Titlebook: Applied Computer Sciences in Engineering; 11th Workshop on Eng Juan Carlos Figueroa-García,German Hernández,Elvis Conference proceedings 20

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書目名稱Applied Computer Sciences in Engineering影響因子(影響力)




書目名稱Applied Computer Sciences in Engineering影響因子(影響力)學(xué)科排名




書目名稱Applied Computer Sciences in Engineering網(wǎng)絡(luò)公開度




書目名稱Applied Computer Sciences in Engineering網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Applied Computer Sciences in Engineering被引頻次




書目名稱Applied Computer Sciences in Engineering被引頻次學(xué)科排名




書目名稱Applied Computer Sciences in Engineering年度引用




書目名稱Applied Computer Sciences in Engineering年度引用學(xué)科排名




書目名稱Applied Computer Sciences in Engineering讀者反饋




書目名稱Applied Computer Sciences in Engineering讀者反饋學(xué)科排名

Stable-Angina

Dorsal-Kyphosis

Social and Environmental Factorsblem. Additionally, we explore?the incorporation of chaotic maps into the binarization process.?To benchmark the binary Fox Optimizer, we compare it with?two well-known and documented metaheuristics: Particle?Swarm Optimization and Grey Wolf Optimizer. Each algorithm is tested?with standard, sine ch

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Sexually transmitted infections and distributing the products to end consumers. In this context, it is proposed to design a model for locating rural centers that serves as logistical support for the yam agri-food supply chain. This location model for hubs aims to plan the distribution in the agri-food supply chain of yams in the

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Sexually transmitted infections sector that is crucial in addressing these challenges. In this context, this work conducted a theoretical review of the optimization techniques used and the information available in a specific case study. From the above, two techniques were selected, linear programming and stochastic linear program

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Natural History of HIV Infectionon approach based on a non-convex cardinality constraint approximation of the ?.-norm to identify the optimal asset weights of the tracking portfolio. The results demonstrate that the ?.-norm-constrained sparse tracking portfolio is computationally efficient and exhibits a notable reduction in track

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