This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the (...) target system. (shrink)

Combinatorial network optimization appears to fit well as a model of brain structure: connections in the brain are a critically constrained resource, hence their deployment in a wide range of cases is finely optimized to “‘save wire". This review focuses on minimization of large-scale costs, such as total volume for mammal dendrite and axon arbors and total wirelength for positioning of connected neural components such as roundworm ganglia (and also mammal cortex areas). Phenomena of good optimization raise questions (...) about mechanisms for their achievement: the examples of optimized neuroanatomy here turn out to include candidates for some of the most complex biological structures known to be derivable purely from simple physical energy minimization processes. Part of the functional role of such fine-tuned wiring optimization may be as a compact strategy for generating self-organizing complex neuroanatomical.. (shrink)

In earlier work, the author has studied the economic role of planning horizons in making a case for complementarity as the predominant feature of social interdependence. This paper compares the different choice strategies implied by substitution, opposition and conflicts of interest in an economics of fear with those arising from horizon effects, economic complementarity and concerts of interest in an economics based on love. The contrasting implications of a psychological literature on negative vs. positive emotions and their health effects, along (...) with the findings in neurophysiological research about how humans are hard-wired for empathy and compassion leads to some fundamental changes in how we might address and revise social problems through economic analysis. The aim of this paper is to extend a horizonal case for complementarity in the author's previous work into its psychological links to research findings on healthy cognitive function and its emotional basis. An economics of substitution yields quite different conclusions about optimal institutional forms and how we address and frame social relations than are implied by an explicitly horizonal economics of complementary social relations. Recent psychological and neurophysiological studies support a horizonal case for complementarity in social relations, showing that our orthodox substitution assumptions and models of competitive equilibrium should be rejected for a renewed economic analysis based on horizonal models of complementarity and cooperation as a means to achieve greater social well-being in a healthier and more integrative form of social organization. The issues to be explored are not entertained within the currently existing frame of orthodox economics, so we must step beyond our standard habitual assumptions. (shrink)

Intervening on causal systems can illuminate their underlying structures. Past work has shown that, relative to adults, young children often make intervention decisions that appear to confirm a single hypothesis rather than those that optimally discriminate alternative hypotheses. Here, we investigated how the ability to make informative causal interventions changes across development. Ninety participants between the ages of 7 and 25 completed 40 different puzzles in which they had to intervene on various causal systems to determine their underlying structures. Each (...) puzzle comprised a three‐ or four‐node computer chip with hidden wires. On each trial, participants viewed two possible arrangements of the chip's hidden wires and had to select a single node to activate. After observing the outcome of their intervention, participants selected a wire configuration and rated their confidence in their selection. We characterized participant choices with a Bayesian measurement model that indexed the extent to which participants selected nodes that would best disambiguate the two possible causal structures versus those that had high causal centrality in one of the two causal hypotheses but did not necessarily discriminate between them. Our model estimates revealed that the use of a discriminatory strategy increased through early adolescence. Further, developmental improvements in intervention strategy were related to changes in the ability to accurately judge the strength of evidence that interventions revealed, as indexed by participants' confidence in their selections. Our results suggest that improvements in causal information‐seeking extend into adolescence and may be driven by metacognitive sensitivity to the efficacy of previous interventions in discriminating competing ideas. (shrink)

This book presents a coherent framework for the balanced development of emotions and cognition throughout the lifespan. It synthesizes rich sources across psychology and neuroscience to show that the brain is hard-wired for basic emotions as well as reasoning, and that these structures mature as individuals learn social rules in interactions with others and progress through complex relationships. In contrast to traditional views that held emotions and cognition to be opposing domains, the author builds on recent views that emphasize the (...) ideal of a cooperative relationship among the two domains. Central to this construct is the fragile balance of expansion and stability that is crucial to both cognitive and affective development: how it can be nurtured for optimal functioning, and how, in contrast, the absence of such a caring context functions to derail growth and encourage pathology that can be carried into later stages of the lifespan. This groundbreaking volume: Traces historical changes in conceptions of the relation between reason and emotion from ancient philosophy to modern science. Expands on Piaget's theories of alternating phases of equilibrium in cognitive development and details how these contribute toward integrated cognitive-emotional growth. Discusses neurobiological mechanisms contributing to balance between emotional and cognitive development. Presents examples of the integration of cognitive/emotional development from infancy to adulthood. Explores the relationships between affect and cognition in later life. Integrating Emotions and Cognition Throughout the Lifespan is an essential resource for researchers, graduate students, and clinicians in a range of disciplines, including developmental psychology, aging, educational philosophy, biological psychology, and personality/social psychology.. (shrink)

- Biological and cognitive systems have the capa- bility of developing new goals during phylogenesis of species or during ontogenesis of single individuals. On the other hand, current artificial cognitive systems focus on how achieving a given fixed set of hard-wired goals. They search an optimal solution of a problem, given a set of goals and a set of optimiza- tion criteria. They look for “how” to achieve a given goal. Natural agents develop new goals in order to cope with (...) par- tially unknown and ever changing environment. They must find “what” they want to achieve and not only “how”. The development of new goals on the basis of the interaction with the environment is here defined the “what” problem. The de- velopment of a collection of goals permits to redefine the con- cept of Umwelt in what could be considered the teleological Umwelt of an agent. The objective of this paper is twofold: i) to outline the “what” problem and ii) to describe a robotic archi- tecture capable of addressing it. (shrink)

It was proposed that the data from Monte Carlo statistical investigations be subjected to analysis of variance methods rather than the conventional techniques of tabling, graphing, and inspecting the data. Two examples in which analysis of variance methods were applied to published Monte Carlo studies were presented. It was suggested that balanced factorial designs should be used whenever possible in Monte Carlo studies so that analysis of variance methods would be directly applicable. Finally, three advantages of analysis of variance methods (...) over conventional techniques were described and analysis of variance methods were contrasted with a possible alternative analytical method, multiple regression analysis. (shrink)

1. 1817-1839. -- 2. 1840-1844. -- 3. 1845-1852 -- 4. 1853-1861. -- 5. 1862-1868 ; Nachträge, 1828-1861.

'Everyone knows what attention is’ according to William James. Much work on attention in psychology and neuroscience cites this famous phrase only to quickly dismiss it. But James is right about this: ‘attention’ was not introduced into psychology and neuroscience as a theoretical concept. I argue that we should therefore study attention with broadly the same methodology that David Marr has applied to the study of perception. By focusing more on Marr's Computational Level of analysis, we arrive at a unified (...) answer to the question of what attention is, what role it plays in the mind, and why organisms like us have that capacity. I propose a methodology for studying attention at Marr's Computational Level that optimizes in a three-dimensional space: it should capture core aspects of our first-person experience of attention, be explanatorily powerful in psychology and neuroscience, and fertile in an interdisciplinary context. I show how this methodology leads to what I call the priority structure account of attention. Attention is what organizes current information to make it more useful for the organism. We can identify it by four features. Attention, in this way, helps a cognitive system to integrate its informational state with its current motivational state. I describe how this account improves on alternatives and shows why attention is a useful concept in many disciplines and for connecting them. -/- This article is categorized under: Philosophy > Psychological Capacities Psychology > Attention Philosophy > Foundations of Cognitive Science. (shrink)

Despite its importance in different occupational and everyday contexts, vigilance, typically defined as the capacity to sustain attention over time, is remarkably limited. What explains these limits? Two theories have been proposed. The Overload Theory states that being vigilant consumes limited information-processing resources; when depleted, task performance degrades. The Underload Theory states that motivation to perform vigilance tasks declines over time, thereby prompting attentional shifts and hindering performance. We highlight some conceptual and empirical problems for both theories and propose an (...) alternative: the Strategic Allocation Theory. For the Strategic Allocation Theory, performance on vigilance tasks optimizes as a function of intrinsic and extrinsic motivations, including metacognitive factors such as the expected value of effort and the expected value of planning. Limited capacities must be deployed across task sets to maximize expected reward. The observed limits of vigilance reflect changes in the perceived value of, among other things, sustaining attention to a task rather than attending to something else. Drawing from recent computational theories of cognitive control and meta-reasoning, we argue that the Strategic Allocation Theory explains more phenomena related to vigilance behavior than other theories, including self-report data. Lastly, we outline some of the testable predictions the theory makes across several experimental paradigms. (shrink)

The biological sciences have become increasingly reliant on so-called 'model organisms'. I argue that in this domain, the concept of a descriptive model is essential for understanding scientific practice. Using a case study, I show how such a model was formulated in a preexplanatory context for subsequent use as a prototype from which explanations ultimately may be generated both within the immediate domain of the original model and in additional, related domains. To develop this concept of a descriptive model, I (...) focus on use of the nematode worm Caenorhabditis elegans and the wiring diagrams that were developed as models of its neural structure. In addition, implications of the concept of a descriptive model, particularly its relevance for the data-phenomena distinction as well as its relation to long-standing debates on realism, are briefly examined. (shrink)

Visual cryptography is a cryptographic technique that allows visual information to be encrypted so that the human optical system can perform the decryption without any cryptographic computation. The halftone visual cryptography scheme (HVCS) is a type of visual cryptography (VC) that encodes the secret image into halftone images to produce secure and meaningful shares. However, the HVC scheme has many unsolved problems, such as pixel expansion, low contrast, cross-interference problem, and difficulty in managing share images. This article aims to enhance (...) the visual quality and avoid the problems of cross-interference and pixel expansion of the share images. It introduces a novel optimization of color halftone visual cryptography (OCHVC) scheme by using two proposed techniques: hash codebook and construction techniques. The new techniques distribute the information pixels of a secret image into a halftone cover image randomly based on a bat optimization algorithm. The results show that these techniques have enhanced security levels and make the proposed OCHVC scheme more robust against different attacks. The OCHVC scheme achieves mean squared error (MSE) of 95.0%, peak signal-to-noise ratio (PSNR) of 28.3%, normalized cross correlation (NCC) of 99.4%, and universal quality index (UQI) of 99.3% on average for the six shares. Subsequently, the experiment results based on image quality metrics show improvement in size, visual quality, and security for retrieved secret images and meaningful share images of the OCHVC scheme. Comparing the proposed OCHVC with some related works shows that the OCHVC scheme is more effective and secure. (shrink)

Standard game theory struggles to explain cooperation and coordination in collective action problems where rational strategies often fail to yield mutually beneficial outcomes. One response to this is team reasoning, which introduces group agency. Another is Kantian optimization, which retains individual agency but assumes universalization-based optimization. Some have proposed that Kantian optimization is best understood as a subtype of team reasoning, a member of the same theoretical family. This paper disputes that. By demonstrating that Kantian-style team reasoning (...) does not necessarily lead to Kantian equilibrium, the paper concludes that Kantian universalization does not fit within the group agency framework. (shrink)

This study investigates the multifaceted impacts of artificial intelligence (AI) on organizational management within international companies operating in Tunisia. Using a quantitative methodology, data were collected from 270 managers and employees across diverse enterprises. The findings reveal that AI significantly enhances managerial tasks by automating repetitive processes and fostering autonomy, confirming its role as an optimization tool. Interestingly, AI positively influences interpersonal relationships, exceeding initial expectations of potential negative impacts. However, its effects on organizational culture are negligible. Ethical and (...) legal concerns, though significant, remain moderate, reflecting growing awareness of challenges related to data protection and decision-making transparency. These results highlight the nuanced role of AI in shaping managerial practices and emphasize the need for organizations to adopt balanced strategies that leverage its benefits while addressing its ethical and relational implications. Future research should focus on longitudinal studies to explore AI’s long-term effects and examine contextual factors influencing its integration into diverse organizational settings. (shrink)

Architectures that maintain representations through continuous recursive updating cannot generate their own termination conditions. No component individuated by participation in that updating occupies a position from which the process could be halted: a stop instruction is either absorbed as content or amounts to component withdrawal. Stopping is imported: from specified priors, from homeostatic machinery, from exhausted resources. Which architectures these are is settled by whether interruption is followed by rebuilding rather than resumption. They do not merely fail to stop. As (...) environmentally grounded gradients are exhausted, optimization is redirected onto internally generated distinctions, producing relational overfitting: internal coherence rises while referential traction falls. This regime is termed epistemic idling; the divergence between local efficiency and global epistemic yield, the Efficiency Paradox. Predictive processing is the setting, not the target. It does not predict attenuation but prevents it by supplying priors and an information-gain term. Those provisions are imports; its own remedy for unbounded structural growth, Bayesian model reduction, is an operation on the model rather than of it. Sleep instantiates the argument rather than refuting it. Reasoning models overcompute on problems that no longer constrain them, exhibiting the signature without settling the thesis. Three predictions follow, two on systems that already exist. (shrink)

This paper will be concerned with hard choices—that is, choice situations where an agent cannot make a rationally justified choice. Specifically, this paper asks: if an agent cannot optimize in a given situation, are they facing a hard choice? A pair of claims are defended in light of this question. First, situations where an agent cannot optimize because of incompleteness of the binary preference or value relation constitute a hard choice. Second, situations where agents cannot optimize because the binary preference (...) or value relation violates acyclicity do not constitute a hard choice. (shrink)

The rapid advancement of eVTOL technology offers a novel solution for enhancing commuting efficiency across complex geographical barriers, thereby accelerating the construction and development of 3D transportation infrastructure. However, the planning and development of an eVTOL operational network rely heavily on detailed passenger flow analysis and strategic decision-making regarding flight frequencies. This paper integrates the classic Multinomial Logit model from transportation planning to estimate route-specific passenger demand. With the objective of maximizing the global unit profit for the eVTOL operator, an (...) optimization model for flight frequency scheduling is established. A Genetic Algorithm, tailored to the model's structure, is designed to calculate the dispatch headways for eVTOLs on each route. A case study, based on the "Xiangtan Urban Area - Zhuzhou West Railway Station - Xiangtan North Railway Station" bidirectional loop eVTOL network, validates the approach. The optimal flight frequencies for each route are derived through computations that account for competition with various transportation modes. Sensitivity analysis reveals that operators must prioritize marketing effectiveness for highly time-sensitive passengers. Furthermore, performing more flexible, dynamic flight adjustments based on accurate predictions of commuter flow is essential for comprehensively improving operational performance. (shrink)

Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become readily available to most people, optimization and optimized processes play a very broad role in societies. It is not obvious, however, that the optimization processes that work for mathematics and abstract objects should (...) be readily applied to complex and open social systems. In this paper we set forth a framework to understand when optimization is limited, particularly for complex and open social systems. (shrink)

We design and implement an intelligent IoT-based motion monitoring system to realize the monitoring of three important parameters, namely, the type of movement, the number of movements, and the period of movement in physical activities, and optimize the system to support the simultaneous use by multiple users. Considering the motion monitoring scenario for smart fit, the framework of an IoT-based motion monitoring system is proposed. The framework contains components such as active acquisition nodes, wireless access points, data processing servers, and (...) terminals. In terms of algorithm optimization, research related to active pattern recognition and periodic calculation methods is conducted. For active pattern recognition, two types of classification algorithms with different complexity are proposed based on Support Vector Machine and deep neural networks, respectively, to adapt to scenarios with different computational capabilities. For period calculation, a method based on over-zero detection and wavelet transform is proposed to count the number of actions and calculate the period of each action. In 100 times action cycle calculation experiments, the count statistic calculation method achieves 100% calculation accuracy and the active cycle calculation results are close to the real value, which proves the effectiveness of the cycle calculation method. The system provides a multiuser-oriented communication method and realizes accurate and reliable human movement monitoring, which has a wide application prospect in the fields of physical education and rehabilitation training. (shrink)

As a universal language in the world, English has become a necessary language communication tool under the globalization of trade. Intelligent, efficient, and reasonable English language-assisted learning system helps to further improve the English ability of language learners. English online learning dictionary, as an important query tool for English learners, is an important part of English online learning. This paper will optimize the design of English online learning dictionary system based on multiagent architecture. Based on the hybrid multiagent cooperative algorithm, (...) this paper will improve the disadvantages of the online English learning dictionary system and propose an appropriate dictionary application evaluation function. At the same time, an improved reinforcement learning algorithm is introduced into the corresponding English online learning dictionary navigation problem so as to improve the efficiency of the online English learning dictionary system. English online learning dictionary is more intelligent and efficient. In this paper, the new online learning dictionary system optimization algorithm is proposed and compared with the traditional system algorithm. The experimental results show that the algorithm proposed in this paper solves the collaborative confusion problem of English learning online dictionary to a certain extent and further solves the corresponding navigation problem so as to improve the efficiency. (shrink)

With the widespread application of deep learning in various domains, the demand for computational resources and training efficiency is growing exponentially. Cloud computing, with its robust computational power and flexible resource scheduling, has become a crucial platform for distributed deep learning training. However, existing distributed training methods still face challenges such as uneven task scheduling, excessive communication overhead, and low resource utilization. This paper proposes an optimization strategy for distributed deep learning training in cloud environments, encompassing dynamic task allocation, (...) data partitioning and caching optimization, communication efficiency improvement, and heterogeneous resource scheduling methods. Experimental validation on typical cloud computing platforms with various deep learning tasks demonstrates that the proposed strategies significantly reduce training time, improve resource utilization, and effectively minimize communication overhead, providing strong support for the efficient execution of cloud-based deep learning tasks. (shrink)

Freight transportation plays a critical role in improving company performance in the modern manufacturing industry. To reduce costs, companies must take advantage of the use of large vehicles. It caused fewer deliveries, but inventory costs and degradation quality are high. One of the joint economic lot size problems in supply chain is Integrated Single-Vendor Single-Buyer Inventory Problem. This study developed the I-SVSB-IP model that considers raw materials’ exponential quality degradation and transportation costs. The objective function of this research was to (...) maximize the Joint Total Profit. Three decision variables used were inventory cycle time, raw material ordering frequency, and frequency of delivery of finished products to buyers. This study proposed a sophisticated Chimp Optimization Algorithm procedure to solve the I-SVSB-IP problem. A case study on the food industry in Indonesia was presented to optimize the I-SVSB-IP. The results showed that the ChOA procedure had produced an optimal solution compared to the state-of-the-art algorithm. This study also demonstrated a sensitivity analysis of decision and transportation variables to cost, revenue, and JTP. The results show that increasing transport frequency of ordering raw materials and finished products to buyers enhances the total cost and reduces joint total profit. In addition, increasing the rate of quality degradation of raw materials reduces JTP. (shrink)

For enhancing the stability of the microgrid operation, this paper proposes an optimization model considering the small-signal stability constraint. Due to the nonsmooth property of the spectral abscissa function, the droop controller parameters’ optimization is a nonsmooth optimization problem. The Sequential Quadratic Programming with Gradient Sampling is implemented to optimize the droop controller parameters for solving the nonsmooth problem. The SQP-GS method can guarantee the solution of the optimization problem globally and efficiently converges to stationary points (...) with probability of one. In the current iteration, the gradient of the nonsmooth function can be evaluated on a set of randomly generated nearby points by computing closed-form sensitivities. A test on the microgrid system shows that the optimality and the efficiency of the SQP-GS are better than those of the heuristic algorithms. (shrink)

This work is developed to improve the current quality of e-commerce logistics services. From the perspective of multiple consumer psychology, based on e-commerce, consumer psychology, and other related theories, vegetable e-commerce B is selected as the research object. The commodity quality, accuracy, and timeliness of commodity distribution and other factors of e-commerce B are discussed through questionnaire survey. Then, according to customers’ opinions about “e-commerce B’s distribution and professional aspects that need to be improved,” the research is conducted. Finally, the (...) direction of follow-up optimization is proposed from four different perspectives of multiple consumption psychology. The research results show that more than 89% of the surveyed customers believe that e-commerce B does a good job in terms of commodity quality, accuracy, and timeliness of commodity distribution, and has a high level of logistics service. However, 26.34% of customers hope that e-commerce B can strengthen the protection of personal privacy, 24.97% hope that the platform can add “delay insurance” for goods, and 39.54% hope that the logistics information of purchased goods can be updated in real time. Therefore, e-commerce B needs to be optimized and improved continuously in the future development. Therefore, research on the optimization of logistics service quality of e-commerce is performed under multiple consumption psychology, which provides certain help for the rapid development of subsequent e-commerce. (shrink)

Companies take project-based management as their organizational strategy, and project quality assurance plays a vital role in improving customer satisfaction and enhancing corporate image. Starting from the perspective of optimizing project quality, this paper assigns different quality influencing factors to each project and each task of the project, divides the labor resources shared by multiple projects in the enterprise according to the skill level, and transforms the problem of project quality optimization. The problem of the highest skill level of (...) labor resources allocated to all projects of the enterprise is designed, and algorithms are designed to achieve the optimization of project quality through the optimal allocation of labor resources. The various links in this article are closely related to form a comprehensive, scientific, and systematic research system for optimal human resource allocation, human resource management, and development. Finally, case analysis is used to confirm the usability of the model and provide a quantitative method and perspective for project-oriented companies to allocate workforce. (shrink)

In this paper, to solve the problem of slow design of arts and crafts and to improve design efficiency and aesthetics, the existing big data and 3D technology are used to conduct an in-depth analysis of the optimization of the rapid design system of arts and crafts machine salt baking. In the system requirement analysis, the functional modules of this system are identified as nine functional modules such as design terminology management system and external information import function according to (...) the actual usage requirements. In the system design, the overall structure design, database design, and functional module design of the system are comprehensively elaborated, and the key issues such as 3D display and home layout generation algorithm based on reinforcement learning are analyzed and designed. In the implementation part of the system, the overall construction of the system and the composition of functional modules are introduced in detail and the main functional modules of the system are presented with interface diagrams. In the system implementation part, the overall system construction and functional module composition are introduced in detail, the main functional modules of the system are shown with interface diagrams, codes, and algorithms, and the specific implementation process of 3D display and soft layout algorithms are also explained in detail. The process of Surface Mount Technology big data processing and analysis is designed, and the design of SMT production line data collection scheme and real-time data processing architecture is completed. Based on the characteristics of SMT production line data, the K-means algorithm is used to detect data outliers and verify the accuracy of the method; also, the Spark-based association rule printing parameter recommendation model is designed, and the efficiency of the Apriori algorithm is significantly improved by parallelization. (shrink)

The conventional community sports facility allocation methods have high minimum costs, and a new community sports facility allocation performance optimization method is designed based on a linear programming model in order to reduce the performance capital investment. The standardized community sports facility allocation performance objective function is established, and a pairwise model is built to divide the feasible and optimal solutions, and the feasible solutions and their constraints are found out. Establish a community sports facility configuration performance optimization (...) model, delineate the boundaries of the optimal solution by bifurcation, and set the feasible domain of the performance optimization model. The performance optimization algorithm is designed to improve the speed of community sports facility allocation performance optimization. In the experiment, the method is compared with data-driven method, digital management method, and evolutionary game algorithm, which requires less capital investment in spring, autumn, and winter than digital management method and evolutionary game algorithm, and the minimum capital investment in summer is less than the other three methods. From the above experimental data, it is clear that the performance optimization method has the smallest minimum capital investment and achieves the purpose of reducing the input cost. (shrink)

Based on the Internet of Things technology, this paper proposes building a cross-border e-commerce logistics supervision system and determines the evaluation index system from the overall framework design of the system, supply chain supervision process optimization, risk supervision optimization, and system order degree optimization. First of all, the framework adopts the national certification center to supervise the logistics service platform and logistics service platform to supervise the logistics participants of the secondary supervision system. Then, functions such as (...) swarm intelligence contract, legal anonymous identity authentication, intelligent transaction matching, abnormal data analysis and detection, privacy protection, and traceability are realized under the framework of the supervision system. Then, the security analysis and transaction supervision component software are used to verify the security, control, and operating efficiency of the transaction supervision framework. Finally, in a real crowd sourcing logistics enterprise platform to run on the software component, the actual measurement, the measured results show that the proposed cross-border supervision system is safe and controllable, and electronic business logistics protects users and data privacy, prevents forgery and fraud, and realizes the user behavior and user data in addition to auditability and traceability. (shrink)

This paper introduces the basic principle and application process of simulated annealing algorithm and improves the simulated annealing algorithm so that it can converge faster to get the new parameters of cultural and creative product design and make it more in line with the reality of engineering optimization. In the cultural creative industry, it is necessary to use the creatorʼs creativity and technology to derive and develop the original cultural resources with the help of various materialization means, to refine (...) the abstract and profound contents of cultural resources to make them more visualized, and to produce products with both spiritual and economic values through the multiple development and utilization of their intellectual property contents. By studying the feasibility analysis of the cultural and creative design, the design positioning of the cultural and creative products is determined. In this article, we use the simulated annealing method to simulate and analyse the condition values in the design process of cultural creative products. As the Internet era progresses, people have more diversified requirements for cultural and creative products, and they need to have innovative ideas to follow the trend, so the design of cultural and creative products can spread culture through different design expressions and media. As one of the important pillar industries for future development, cultural and creative products are characterized by a wide range of styles and practicality, which meet the aesthetic needs and fashion trends of modern people. (shrink)

This study is to explore the optimization of the adaptive genetic algorithm in the backpropagation neural network, so as to expand the application of the BPNN model in nonlinear issues. Traffic flow prediction is undertaken as a research case to analyse the performance of the optimized BPNN. Firstly, the advantages and disadvantages of the BPNN and genetic algorithm are analyzed based on their working principles, and the AGA is improved and optimized. Secondly, the optimized AGA is applied to optimize (...) the standard BPNN, and the optimized algorithm is named as OAGA-BPNN. Finally, three different cases are proposed based on the actual scenario of traffic flow prediction to analyse the optimized algorithm on the matrix laboratory platform by simulation. The results show that the average error distribution of the GA-BPNN algorithm is about 1% with small fluctuation range, better calculation accuracy, and generalization performance in contrast to the BPNN. The average output error of the AGA-BPNN fluctuates around 0 and remains in a relatively stable range as a whole in contrast to that of GA-BPNN; the maximum fitness level keeps increasing during the evolution process but approaches the average value in later process, so the population diversity is hard to be guaranteed. The output error of the OAGA-BPNN fluctuates little compared with that of AGA-BPNN, and its maximum fitness continues to increase in the evolution process with guaranteed population diversity. In short, the OAGA-BPNN algorithm can achieve the best performance in terms of calculation accuracy, generalization performance, and population evolution. (shrink)