RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. …”
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Electric Vehicle Charging Load Forecasting Method Based on Improved Long Short-Term Memory Model with Particle Swarm Optimization by Xiaomeng Yang, Lidong Zhang, Xiangyun Han

“…By combining the global search capability of the PSO algorithm with the advantages of LSTM networks in time-series modeling, a PSO-LSTM hybrid framework optimized for seasonal variations is developed. …”
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Stochastic sizing and energy management of a hybrid energy system using cloud model and improved Walrus optimizer for China regions by Wenjun Liao, Qing Xiong, Zilong Chen, Jinhui Tan, Pingfei Li, Hadi Gharoei

“…An improved Walrus Optimizer (IWO) with a piecewise linear chaotic map is applied to determine the optimal system component sizes. …”
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Edge server deployment decision based on improved NSGA-Ⅱ in the Internet of vehicles edge computing scenario by Sifeng ZHU, Yu WANG, Hao CHEN, Hai ZHU, Zhengyi CHAI, Chengrui YANG

“…In the context of the Internet of vehicles, the placement and deployment number of edge servers directly affect the efficiency of edge computing.Due to the high cost of deploying a large edge server on a macro base station and a base station, it can be complemented by deploying a small edge server on a micro base station, and the cost reduction needs to be optimized by optimizing the placement of large edge servers.In order to minimize the deployment cost and service delay of the edge server, and maximize the operator’s revenue and server load balance, the edge server placement problem combined with the vehicle networking user application service was modeled as a multi-objective optimization problem and a placement scheme based on improved NSGA-Ⅱ algorithm was proposed.The experimental results show that the proposed scheme can reduce the deployment cost of edge servers by about 44%, the latency by about 14.2%, and improve the revenue of operators by 24.2%, which has good application value.…”
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Improved and Optimized GNSS-IR Sea Surface Height Retrieval Based on Noise Elimination and Lightweight Airborne Multi-GNSS Multi-UAV Fusion by Naiquan Zheng, Ying Xu, Fuxi Zhao, Mingzhen Xin, Fanlin Yang

“…In summary, the improved model based on noise elimination and the optimized model of airborne multi-GNSS multi-UAV collaborative fusion can obtain robust, reliable results.…”
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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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An Immune Algorithm based Reliability Optimization Method of Circuit Board by XIA Quan, REN Yi, SUN Bo, WU Zeyu

“…This method is applied to solve the reliability optimization model of typical circuit boards, and the optimization scheme of design variables is obtained.The results are compared with genetic algorithm and ant colony algorithm.It shows that the immune algorithm has the advantages of fast convergence speed and strong optimization ability.Moreover, the calculation time is reduced by about 37.2% by the collaborative optimization strategy in the case.Thus, the collaborative optimization method based on immune algorithm proposed in this paper can effectively improve the solution efficiency of circuit board reliability optimization model.…”
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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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DEVELOPMENT OF THE ALGORITHM FOR CHOOSING THE OPTIMAL SCENARIO FOR THE DEVELOPMENT OF THE REGION'S ECONOMY by I. S. Borisova

“…It was found that the rationale and choice of the optimal scenario is an important stage in the development of the sustainable development program of the regional economy, since it helps to quantify the most probable trajectories of changes in the activities of all participants in the region's economy.Conclusions and Relevance: the practical significance of the developed algorithm lies in the possibility of using it to improve the stability of the development of the economy of specific regions. …”
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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

“…Our method outperforms the genetic algorithm (GA), Particle Swarm Optimization (PSO), and the slime mould algorithm (SMA), as well as deep learning-based skin cancer classification models, which have reported accuracies of 87% to 94% in previous studies. …”
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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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Building Construction Design Based on Particle Swarm Optimization Algorithm by Wenxue Song

“…The relationship between the various risk factors was described by conditional probability, and a safety risk loss-control investment double objective optimization model was built. The corresponding algorithm was designed and the R language programming was used to solve the problem. …”
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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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Optimization of Selective Laser Sintering Processing Parameters Based on ISMA-ELM Hybrid Model by LI Jian, NIE Qian, JIANG Chenglei, GUO Yanling, WANG Yangwei

“…Simulation results demonstrate that the proposed ISMA-ELM obtains optimal prediction results compared to the standard and other algorithm-optimized ELM models. …”
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Improved Grey Wolf Algorithm: A Method for UAV Path Planning by Xingyu Zhou, Guoqing Shi, Jiandong Zhang

“…Subsequently, an Enhanced Grey Wolf Optimizer model (NI–GWO) is introduced, which optimizes the convergence coefficient using a nonlinear function and integrates the Dynamic Window Approach (DWA) algorithm into the model based on the fitness of individual wolves, enabling it to perform dynamic obstacle avoidance tasks. …”
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A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition by Cai Dai, Xiujuan Lei

“…Some multiobjective brain storm optimization algorithms have low search efficiency. This paper combines the decomposition technology and multiobjective brain storm optimization algorithm (MBSO/D) to improve the search efficiency. …”
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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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Research on trajectory planning method for food sorting robot based on machine vision and improved BOA by CUI Wei, YUAN Rui, SUN Litao, WANG Wei

“…By improving the butterfly optimization algorithm, the optimal solution for the motion trajectory of the parallel robot was obtained and its superiority was verified.ResultsCompared with conventional methods, the proposed trajectory optimization method had better operational efficiency and control effects, with the more smoother of the planned trajectory. …”
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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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