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The times are advancing, the Internet is constantly advancing, and there are many examples of the combination of technology and life. The way people buy agricultural products is no longer limited to the physical market, but is being transformed into an agricultural product e-commerce website to achieve digital transformation. So far, a large number of agricultural products have been collected on the agricultural product e-commerce website, they come from all over the country, and different types and different regional agricultural products have appeared. On the other hand, users are faced with a large number of commodities on the Internet. If they simply use search engines, consumers need to spend a lot of time to find the commodities they are interested in by browsing. Searching from the recommended ones greatly reduces the product set and optimizes the performance of the e-commerce platform. Therefore, the generation of the personalized recommendation system meets the needs of the market. This research will improve the related recommendation algorithm by improving the user similarity calculation method based on artificial intelligence technology, improve the execution efficiency and accuracy of the improved algorithm, and use related technologies to develop an agricultural product e-commerce recommendation system. It has important theoretical and practical significance to save users' browsing time, improve users' shopping experience, and speed up the construction of agricultural product e-commerce., Author(s): FengQin ZhuanSun (corresponding author) [1]; JiaoJiao Chen [1]; Wenlong Chen [1]; Yan Sun [1] 1. Introduction With the continuous advancement of the Internet, cloud computing, and big data technologies, [...]

Abstract--This paper presents consciousness as the sure of describable processes, without limiting it only to verbal understanding. Consciousness is presented as a buffer space of the unconscious, accessed by any [...]

Green Vehicle Routing Optimization Problem (GVROP) is currently a scientific research problem that takes into account the environmental impact and resource efficiency. Therefore, the optimal allocation of resources and the carbon emission in GVROP are becoming more and more important. In order to improve the delivery efficiency and reduce the cost of distribution requirements through intelligent optimization method, a novel multiobjective hybrid quantum immune algorithm based on cloud model (CHQIA) is put forward. Simultaneously, the computational results have proved that the C-HQIA is an efficient algorithm for the GVROP. We also found that the parameter optimization of the C-HQIA is related to the types of artificial intelligence algorithms. Consequently, the GVROP and the C-HQIA have important theoretical and practical significance., 1. Introduction With the increasing global average temperature and global energy tension, climate change has become a global concern. Energy saving and emission reduction have become a common responsibility of [...]

Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based) model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to be addressed. In this study, a new energy demand forecasting framework is presented at first. On the basis of historical annual data of electricity usage over the period of 1985-2015, the coefficients of linear and quadratic forms of the AI-based model are optimized by combining an adaptive genetic algorithm and a cointegration analysis shown as an example. Prediction results of the proposed model indicate that the annual growth rate of electricity demand in China will slow down. However, China will continue to demand about 13 trillion kilowatt hours in 2030 because of population growth, economic growth, and urbanization. In addition, the model has greater accuracy and reliability compared with other single optimization methods., 1. Introduction Energy, which is a vital input for the economic and social development of any economy, has gained special attention. Combined with globalization and industrialization, global energy demand has [...]

This article deals with a methodology of using up-to-date mathematical and informational techniques to control the human immune system. Through the example of mathematically controlled HIV therapy, prospects are demonstrated for technologies that have never been used in medicine. The results indicate the possibility of significant advances in prolonging the life of HIV-infected people with the aid of mathematical technologies, which allow reducing the amount of chemotherapy., UDC 519.95 1. Introduction Section 3 of the present article demonstrates the two limiting regimes of the dynamic simulation of HIV infection caused by the human immunodeficiency virus. Reflecting the [...]

The random assignment problem asks for the minimum-cost perfect matching in the complete n x n bipartite graph [K.sub.nn] with i.i.d, edge weights, say uniform on [0, 1]. In a [...]

Many everyday occurrences entail two or more elements that are associated by some rule of correspondence. The mathematical term for such a correspondence is a relation. Within the stimulus equivalence [...], Fifteen participants unfamiliar with mathematical operations relative to reflections and vertical and horizontal shifts were exposed to an introductory lecture regarding the fundamentals of the rectangular coordinate system and the relationship between formulas and their graphed analogues. The lecture was followed immediately by computer-assisted instructions and matching-to-sample procedures in which participants were exposed to computer-posted rules regarding the relationship between particular types of formulas and their respective graphs. After participants demonstrated mutual entailment on formula-to-graph and graph-to-formula functions, they were assessed for 36 novel relations on complex variations of the original training formulas and graphs. In Experiment 1, 5 of 15 participants demonstrated perfect or near perfect performance on all novel relationships. Experiment 2 was directed at the remaining 10 participants who failed to correctly identify all mathematical relationships assessed in Experiment 1. The error patterns for these 10 participants were classified with the help of an artificial neural network self-organizing map (SOM). Training in Experiment 2 was directed exclusively at the types of errors identified by the SOM. Following remedial training, all participants demonstrated a substantial reduction in errors compared to their performance in Experiment 1. Derived transfer of stimulus control using mathematical relations is discussed.

Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher [...]