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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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…In this paper, a new method is proposed to classify and distinguish a group of eight different plants to healthy and unhealthy based on the leaf images of these plants They are apples, cherries, grapes, peaches, peppers, potatoes, strawberries, and tomatoes using a hybrid optimization algorithm. In the first stage, the plant leaf images were collected and pre-processed to remove noise and improve contrast. …”
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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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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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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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Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

“…For future research, it is recommended to explore the combination of SVR with optimization techniques such as genetic algorithms to further improve the accuracy of soil texture and color predictions.…”
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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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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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Simulated Annealing-Based Krill Herd Algorithm for Global Optimization by Gai-Ge Wang, Lihong Guo, Amir Hossein Gandomi, Amir Hossein Alavi, Hong Duan

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Simple gravitational particle swarm algorithm for multimodal optimization problems. by Yoshikazu Yamanaka, Katsutoshi Yoshida

“…Aiming to help the decision makers even if they are non-experts in optimization algorithms, this study proposes a new and simple multimodal optimization (MMO) algorithm called the gravitational particle swarm algorithm (GPSA). …”
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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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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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