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1. An Adaptive Bacterial Foraging Optimization Algorithm Based on Chaos-Enhanced Non-elite Reverse Learning NSTL国家科技图书文献中心

Yibo Yong | Lianbo Ma ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 133～144 - 共12页

摘要：Bacterial Foraging Optimization Algorithm (BFO | ) is a swarm intelligence-based optimization | algorithm that has been widely applied in various fields | . However, the classical BFO still suffers from two major | limitations: The fixed chemotactic step-size makes it

关键词： Bacterial foraging optimization algorithm | Adaptive chemotactic step-size | Chaos-enhanced non-elite reverse learning

2. Diversity Improved Genetic Algorithm for Weapon Target Assignment NSTL国家科技图书文献中心

Nianfeng Weng | Yi Liu ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 366～378 - 共13页

摘要：There are many optimization problems in | military applications, among which the weapon target | assignment (WTA) problem is the most typical and the most | widely studied problem. Plenty of evolutionary | algorithms-based methods are studied for resolving it

关键词： Weapon target assignment | Genetic algorithm | Diversity enhanced mechanism | Levy flight mutation | Hybrid crossover

3. Set-Based Particle Swarm Optimization for the Multi-objective Multi-dimensional Knapsack Problem NSTL国家科技图书文献中心

Mari Spangenberg | Andries Engelbrecht - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 3～19 - 共17页

摘要：The set-based particle swarm optimization | algorithm (SBPSO) was developed to solve the single | -objective multi-dimensional knapsack problem. Since then | , the SBPSO was applied to a number of, mostly single | -objective, optimization problems. Recently, the SBPSO was

关键词： Multi-objective multi-dimensional knapsack problem | Particle swarm optimization | Set-based particle swarm-optimization

4. Multi-strategy Enhanced Particle Swarm Optimization Algorithm for Elevator Group Scheduling NSTL国家科技图书文献中心

Chen Zhang | Mingli Lu ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 58～69 - 共12页

摘要：Although particle swarm optimization has shown | great potentials in solving the complex elevator group | scheduling problem, it still suffers from the issue of | local optimum. In order to improve the capability of | finding the global optimum, a multi-strategy enhanced

关键词： Elevator group scheduling | Particle swarm optimization | Tent mapping | Spiral flight strategy | Local search strategy

5. A Joint Prediction Strategy Based on Multiple Feature Points for Dynamic Multi-objective Optimization NSTL国家科技图书文献中心

Yaxin Li | Li Yan ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 403～417 - 共15页

摘要：This paper proposes a joint prediction | strategy based on multiple feature points (JP-MFP) to | improve the prediction accuracy and balance the | convergence and diversity. On the one hand, a multi-step | prediction based on center points is designed to generate

关键词： Dynamic multi-objective optimization | Joint prediction | Feature points

6. Stock Price Prediction Model Based on Blending Model Improved with Sentiment Factors and Double Q-learning NSTL国家科技图书文献中心

Maoguang Wang | Yuxiao Chen ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 325～337 - 共13页

摘要：Stock market prediction is of paramount | importance for economic decision-makers and investors | . Traditional approaches often rely on single indicators or | sentiment analysis techniques, which may limit their | ability to capture the complexity of market dynamics. In

关键词： Ensemble learning | Sentiment factors | Double q-learning | Stock price fluctuation prediction

7. Research on the Basic Combat Round Model of Over-The-Horizon Air Combat NSTL国家科技图书文献中心

Mao Dejun | Yang Ling - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part II》 - International Conference on Swarm Intelligence - 2024, - 375～379 - 共5页

摘要：The Basic Fight Circle (BFC) refers to the | process in which one or both sides completely carry out | a missile attack and defense in a fighter medium | -range air combat with air-to-air missiles as weapons | . A basic combat round usually includes, but is not

关键词： Over-the-horizon air combat | The basic combat round model | Research

8. An Investigation of Underground Rescue Scheduling with Multi-agent Reinforcement Learning NSTL国家科技图书文献中心

Xuge Li | Yueyun Zhong ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part I》 - International Conference on Swarm Intelligence - 2024, - 379～390 - 共12页

摘要：Underground rescue scheduling poses | substantial challenges due to unknown environment and low | visibility. The task inherently involve multi-agent systems | and pose significant complexities. In this paper, we | focus on simulating underground rescue missions by

关键词： Underground rescue | Full-term multi-agent reinforcement learning | Curiosity-driven

9. ESEC: A New Edge Server Selection Algorithm Under Multi-access Edge Computing NSTL国家科技图书文献中心

YingHui Yang | XianJi Wang ... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part II》 - International Conference on Swarm Intelligence - 2024, - 323～337 - 共15页

摘要：In multi-access edge computing, offloading | tasks to edge nodes can effectively reduce the | computing consumption of terminal devices. The traditional | task offloading methods usually select edge node that | are close to terminal equipment as offloading nodes

关键词： MEC | Task offloading | The execution delay of tasks | Load balance

10. New Design Algorithm: Interactive-Generative Product Design for Shape Generation and Optimization NSTL国家科技图书文献中心

Somlak Wannarumon Ki... | Prapasson Pradujphon... - 《Advances in Swarm Intelligence: 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024, Proceedings, Part II》 - International Conference on Swarm Intelligence - 2024, - 353～362 - 共10页

摘要：This paper proposes a new approach of | interactive-generative product design process based on | parametric shape grammar and genetic algorithm. The | proposed design algorithm aims to be used in generating a | set of various design alternatives in early-stage

摘要：Bacterial Foraging Optimization Algorithm (BFO | ) is a swarm intelligence-based optimization | algorithm that has been widely applied in various fields | . However, the classical BFO still suffers from two major | limitations: The fixed chemotactic step-size makes it

关键词： Bacterial foraging optimization algorithm | Adaptive chemotactic step-size | Chaos-enhanced non-elite reverse learning

摘要：There are many optimization problems in | military applications, among which the weapon target | assignment (WTA) problem is the most typical and the most | widely studied problem. Plenty of evolutionary | algorithms-based methods are studied for resolving it

关键词： Weapon target assignment | Genetic algorithm | Diversity enhanced mechanism | Levy flight mutation | Hybrid crossover

摘要：The set-based particle swarm optimization | algorithm (SBPSO) was developed to solve the single | -objective multi-dimensional knapsack problem. Since then | , the SBPSO was applied to a number of, mostly single | -objective, optimization problems. Recently, the SBPSO was

关键词： Multi-objective multi-dimensional knapsack problem | Particle swarm optimization | Set-based particle swarm-optimization

摘要：Although particle swarm optimization has shown | great potentials in solving the complex elevator group | scheduling problem, it still suffers from the issue of | local optimum. In order to improve the capability of | finding the global optimum, a multi-strategy enhanced

关键词： Elevator group scheduling | Particle swarm optimization | Tent mapping | Spiral flight strategy | Local search strategy

摘要：This paper proposes a joint prediction | strategy based on multiple feature points (JP-MFP) to | improve the prediction accuracy and balance the | convergence and diversity. On the one hand, a multi-step | prediction based on center points is designed to generate

关键词： Dynamic multi-objective optimization | Joint prediction | Feature points

摘要：Stock market prediction is of paramount | importance for economic decision-makers and investors | . Traditional approaches often rely on single indicators or | sentiment analysis techniques, which may limit their | ability to capture the complexity of market dynamics. In

关键词： Ensemble learning | Sentiment factors | Double q-learning | Stock price fluctuation prediction

摘要：The Basic Fight Circle (BFC) refers to the | process in which one or both sides completely carry out | a missile attack and defense in a fighter medium | -range air combat with air-to-air missiles as weapons | . A basic combat round usually includes, but is not

关键词： Over-the-horizon air combat | The basic combat round model | Research

摘要：Underground rescue scheduling poses | substantial challenges due to unknown environment and low | visibility. The task inherently involve multi-agent systems | and pose significant complexities. In this paper, we | focus on simulating underground rescue missions by

关键词： Underground rescue | Full-term multi-agent reinforcement learning | Curiosity-driven

摘要：In multi-access edge computing, offloading | tasks to edge nodes can effectively reduce the | computing consumption of terminal devices. The traditional | task offloading methods usually select edge node that | are close to terminal equipment as offloading nodes

关键词： MEC | Task offloading | The execution delay of tasks | Load balance

摘要：This paper proposes a new approach of | interactive-generative product design process based on | parametric shape grammar and genetic algorithm. The | proposed design algorithm aims to be used in generating a | set of various design alternatives in early-stage

关键词： Genetic algorithm | Generative design | Interactive generative design | Mass customization | Product design | Shape grammar

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