Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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Dynamic Node Management for Energy Optimization in Cognitive Radio Systems by Tangsen Huang, Haibing Yin, Xiangdong Yin, Huijun Xiao

“…Nodes with reliability values exceeding a predefined threshold are selected for cooperative spectrum sensing. The selected nodes are divided into two groups using a staggered grouping approach, ensuring equivalent sensing performance between the groups. …”
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Optimization and Decision-Making for a Service Contract on Machine Maintenance by Zeyu Luo, Zhixin Yang, Jinbiao Wu, Zhaotong Lian

“…The service provider of the machine must determine the optimal pricing structure and staffing levels, while the client selects an appropriate plan for the warranty duration. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…Compared with traditional models like the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) and Support Vector Machine (SVM), the proposed framework significantly improves the sensitivity and generalization ability for detecting various types of attacks through dynamic feature selection and parameter optimization. Experimental results demonstrate that the hybrid algorithm exhibits superior real-time responsiveness in binary classification tasks, thanks to its lightweight design that reduces dependency on computational resources. …”
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Selection of emission reduction modes for energy-intensive enterprises under the dynamic carbon cap-and-trade regulation by Chunyi Ji, Binjia Chen, Wei Zhao, Xinyue Wang, Wuyong Qian

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A Genetic Algorithm and PCA-Based Feature Selection to Improve the Failure Diagnosis Performance of Railway Vehicle Doors by Gil Hyun Kang, Ho Cheol Ki, Sang Hyun An, Juhee Choi, Chul Su Kim

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Experiences with the Implementation of Cuban Health Cooperation Programs in Low and Middle-Income Countries: A Scoping Review [version 1; peer review: 1 approved, 2 approved with r... by Faith Njiriri, Jacinta Nzinga, Benjamin Tsofa, Moriasi Nyanchoka

“…Long-term comprehensive programs have proven to be more successful in boosting the healthcare workforce and enhancing health outcomes. Key factors for optimizing HRH health cooperation include effective collaborative decision-making and need-based deployment.…”
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Strategy Selection to Enhance Customer Data Quality using AHP: Case Study of General Insurance Company (PT XYZ) by Adinda Rizkita Syafira, Achmad Nizar Hidayanto, Widijanto Satyo Nugroho, Rahmat Mustafa Samik-Ibrahim

“…The Analytical Hierarchy Process (AHP) is utilized to select the optimal strategy from available alternatives. …”
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Hyperparameter Optimization for Tomato Leaf Disease Recognition Based on YOLOv11m by Yong-Suk Lee, Maheshkumar Prakash Patil, Jeong Gyu Kim, Yong Bae Seo, Dong-Hyun Ahn, Gun-Do Kim

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Optimization of Performance Shaping Factor in SPAR-H Method for Nuclear Power Plant by ZHUO Yucheng1, QIU Yongping1, LIU Peng2, LI Zhizhong3, LEI Wenjing1, TAN Xiao1, QIU Yimin1

“…The PSFs in the optimized SPAR-H method included 9 PSFs: time pressure, stress, complexity, experience/training, procedures, human-machine interface, fatigue, working conditions and team cooperation. …”
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Dynamic Topology Evolution and Multi-Objective Routing Optimization for Efficient VANET Communication by Hao Wang

“…The proposed algorithm utilizes a Dynamic Topology Evolution (DTE) model to evaluate routing stability by capturing continuous changes in network topology. By integrating a cooperative relay mechanism and a multi-objective relay node selection method, the algorithm significantly enhances data transmission success rates and reduces end-to-end latency. …”
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Optimization configuration method of integrated energy system for reliability improvement of distribution network by SHI Mingming, MIAO Huiyu, GUO Jiahao, JIANG Yunlong, XIAO Xiaolong

“…Simulation results show that the proposed method can realize the cooperative optimization of IES and distribution network economy and reliability.…”
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Optimization of vehicle routing problems combining the demand urgency and road damage for multiple disasters by Ran Li, Xiaofei Ye, Shuyi Pei, Xingchen Yan, Tao Wang, Jun Chen, Pengjun Zheng

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A Comprehensive Review on the Integration of Renewable Energy Through Advanced Planning and Optimization Techniques by Carlos Barrera-Singaña, María Paz Comech, Hugo Arcos

“…Emerging international cooperation clusters are identified through quantitative bibliometric analysis, and method selection in practice is illustrated using a table with concise snapshots of case study excerpts. …”
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Optimizing the role of pharmacists at the primary healthcare centres in Indonesia through an integrated information system by Nur Yuliasih, Yasmin Fatinah, Rizky Abdulah, Rizky Abdulah, Auliya A. Suwantika, Auliya A. Suwantika, Auliya A. Suwantika

“…Semi-structured interviews were conducted in four sections (context, content, process, and actors) with consideration of selected key respondents. All interviews were transcribed verbatim and then analyzed using Braun and Clarke’s thematic analyses, ensuring a comprehensive understanding of the situation.ResultsWe identified two significant challenges in optimizing the use of integrated systems at the PHCs to increase the role of pharmacists. …”
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Twin Delayed DDPG (TD3)-Based Edge Server Selection for 5G-Enabled Industrial and C-ITS Applications by Malik Muhammad Saad, Muhammad Ali Jamshed, Abdulhameed Idris Adedamola, Ali Nauman, Dongkyun Kim

“…This paper proposes an AI-driven framework for optimal edge server selection and collaborative load management in 5G-enabled C-ITS and industrial environments. …”
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Optimization of Electrochemical Treatment Process Conditions for Distillery Effluent Using Response Surface Methodology by P. Arulmathi, G. Elangovan, A. Farjana Begum

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AI-strategic game-theoretic analysis of haze management: A study on local government decision-making in China by Jafar Hussain, Benjamin Lev, Zhenyu Qiu, Xinting Ding, Jifan Ren, Jinyi Tian

“…Simulation results indicate that the selection of ST or PT is highly sensitive to variations in economic returns, cost structures, and the degree of cooperative engagement. …”
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Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach by Yueyi Li, Xiaodong Zhang

“…To tackle the challenges in SHCs, we propose a targeted networked solution that integrates multimodal coordination and resource optimization. The proposed framework is built upon a time-space-state network model, incorporating service selection, timing, and frequency decisions. …”
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Prevalence of mental disorders in patients with pathological obesity selected for bariatric surgery in the KOS-BAR nationwide multi-centre pilot programme – a preliminary report by Marta Herstowska, Ada Przygocka-Pieniążek, Karol Grabowski, Łukasz Kaska

“…Psychiatric support can improve patient cooperation and optimize long-term outcomes after bariatric surgery. …”
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