A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

“…Taking into account the multi-modal and multi-variable characteristics of the optimized objective function, we put forth an enhanced version of the improved differential evolution algorithm, the Linear-Chaos and Two Mutation Strategies of Adaptive Differential Evolution (LCTADE)with Covariance Matrix and Cauchy Perturbation(CC-LCTADE). …”
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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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Integrated Optimization System for Geotechnical Parameter Inversion Using ABAQUS, Python, and MATLAB by Chengjie Wan, Nianchun Xu, Jiangchao Meng, Junning Chen

“…To improve the optimization process, an adaptive genetic algorithm that dynamically adjusts crossover and mutation rates, thereby improving solution searches and parameter space exploration, is implemented. …”
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Application of Adaptive Genetic Algorithm in Optimal Scheduling of Aviation Materials by Jinqiu Shang

“…This research establishes the model of air material scheduling problem and introduces NSGA-II genetic algorithm with adaptive design to optimize the air material scheduling arrangement. …”
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An Optimal Algorithm for Renewable Energy Generation Based on Neural Network by Weihua Zhao, Imran Khan, Shelily F. Akhtar, Mujahed Al-Dhaifallah

“…The results show that the proposed algorithm has technological applications and may greatly improve prediction accuracy.…”
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Task Offloading Scheme Based on Proximal Policy Optimization Algorithm by Yutong Ma, Junfeng Tian

“…To address this issue, this paper proposes a task offloading scheme based on the Proximal Policy Optimization (PPO) algorithm. On the basis of traditional cloud edge collaborative architecture, the collaborative computing mechanism between edge node devices is further integrated, and the concept of service caching is introduced to reduce duplicate data transmission, reduce communication latency and network load, and improve overall system performance. …”
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Energy Optimal Control Strategy of PHEV Based on PMP Algorithm by Tiezhou Wu, Yi Ding, Yushan Xu

“…Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP) algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. …”
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Optimization of Heterogeneous Container Loading Problem with Adaptive Genetic Algorithm by Xianbo Xiang, Caoyang Yu, He Xu, Stuart X. Zhu

“…Taking a set of test data given by George and Robinson as strongly heterogeneous data, the space utilization in this paper can be improved by 4.42% in comparison with their heuristic algorithm.…”
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Wind resistance performance optimization of PSO algorithm in skyscrapers design by Wang Shifeng

“…To optimize the skyscrapers and enhance its wind resistance performance under wind load, a wind resistance optimization method for super high-rise building structure on the basis of improved Particle Swarm Optimization (PSO) is built. …”
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Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm by Han Xiaoming, Qian Jingjing

“…A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. …”
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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

“…The random forest algorithm and whale optimization algorithm were introduced in the construction of the prediction model of concrete dam deformation based on WOA-RFR to improve the prediction accuracy and model performance. …”
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Multi-Objective Ore Blending Optimization for Polymetallic Open-Pit Mines Based on Improved Matter-Element Extension Model and NSGA-II by Jun Xiang, Jianhong Chen, Aishu Zhang, Xing Zhao, Shengyuan Zhuo, Shan Yang

“…This study constructs a multi-objective ore blending optimization system for complex polymetallic open-pit mines based on the improved matter-element extension model and NSGA-II algorithm. …”
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Building Construction Design Based on Particle Swarm Optimization Algorithm by Wenxue Song

“…It was concluded that, considering the risk correlation optimization model, a reasonable allocation strategy was adopted, combined with the actual situation, which performed a promoting function in improving the assembly building construction safety risk decision-making.…”
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Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent by Ruslan I. Abdulkadirov, Pavel A. Lyakhov, Valentina A. Baboshina, Nikolay N. Nagornov

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Modified Whale Optimization Algorithm for Multiclass Skin Cancer Classification by Abdul Majid, Masad A. Alrasheedi, Abdulmajeed Atiah Alharbi, Jeza Allohibi, Seung-Won Lee

“…To address these challenges, this paper proposes an innovative deep learning-based framework that integrates an ensemble of two pre-trained convolutional neural networks (CNNs), SqueezeNet and InceptionResNet-V2, combined with an improved Whale Optimization Algorithm (WOA) for feature selection. …”
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GNN-based optimization algorithm for joint user scheduling and beamforming by Shiwen HE, Jun YUAN, Zhenyu AN, Min ZHANG, Yongming HUANG, Yaoxue ZHANG

“…The coordinated multi-point (CoMP) transmission technology has the characteristics of reducing co-channel interference and improving spectral efficiency.For the CoMP technology, user scheduling (US) and beamforming (BF) design are two fundamental research problems located in the media access control layer and the physical layer, respectively.Under the consideration of user service quality requirements, the joint user US-BF optimization problem was investigated with the goal of maximizing network throughput.To overcome the problem that the traditional optimization algorithm had high computational cost and couldn’t effectively utilize the network historical data information, a joint US and power allocation (M-JEEPON) model based on graph neural network was proposed to realize joint US-BF optimization by combining the beam vector analytical solution.The simulation results show that the proposed algorithm can achieve the performance matching or even better than traditional optimization algorithms with lower computational overhead.…”
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User interest-aware content replica optimized placement algorithm by Xiao-long YANG, Xin-xin WANG, Min ZHANG, Ke-ping LONG, Qiong HUANG

“…A user interest-aware content replica optimized placement algorithm (UIARP) is proposed.Firstly,the interest subjects of the user-collective are extracted from their content access logs by clustering algorithms,and according to the weighting of the individual interest degree,their collective interest degree would be got and updated in real time; then under the nonlinear optimization model,replicas of larger collective interest degree have priority to be placed,with the goal of minimizing the average response time,which achieves the maximum match between placing replicas and users’ content demand.This algorithm not only ensures that users get interested replicas quickly,but also improves the system efficiency.From four aspects including average response time,the matching degree of request response,load balancing and the utilization rate of adjacent replicas,using 1-Greedy-Insert or others as compared algorithms,the simulation re-sults show that each metric improves by 30% on average,which verifies the effectiveness of the proposed algorithm.…”
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Overview of Deep Learning Algorithms and Optimizers for Brain Tumor Segmentation by Nisha Purohit, Chandi Prasad Bhatt

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The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model by Jiaxin Wang, Ying Yang, Xian Yang, Yulong Lu, Yang Liu, Da Hu, Yongjia Hu

“…To address the limitations of conventional prediction methods, in this study, we introduce an enhanced predictive model, the improved sparrow search algorithm-optimized extreme learning machine (ISSA-ELM), for accurate karst-collapse susceptibility assessment. …”
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Hare escape optimization algorithm with applications in engineering and deep learning by Doaa Alsamee, Reza Ramezani

“…Abstract The Hare Escape Optimization (HEO) algorithm is a novel metaheuristic inspired by the evasive movement strategies of hares when pursued by predators. …”
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