Wear fault diagnosis in hydro-turbine via the incorporation of the IWSO algorithm optimized CNN-LSTM neural network by Fang Dao, Yun Zeng, Yidong Zou, Jing Qian

“…Chaotic mapping, bird flock search, and cosine elite variation strategies are introduced to enhance the WSO algorithm's robust performance, and the CNN-LSTM model's hyperparameters are optimized using the IWSO algorithm to improve the diagnostic performance. …”
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Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…The ant colony optimization method identified the most relevant feature subsets using a clinical dataset, reducing model complexity while preserving predictive accuracy. …”
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RSM-YOLOv11: Lightweight Steel Surface Defect Segmentation Algorithm Research Based on YOLOv11 Improvement by Zenghai Shan, Hu Haoyan, Changjian Zhu, Shaowen Du, Hongtao Jing, Wang Haibin

“…While maintaining a lightweight structure, it outperforms existing mainstream algorithm models. Additionally, generalization experiments using other types of datasets confirm that the algorithm has good generalization ability.…”
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Ecological and Statistical Evaluation of Genetic Algorithm (GARP), Maximum Entropy Method, and Logistic Regression in Predicting Spatial Distribution of Astragalus sp. by Amir Ghahremanian, Abbas Ahmadi, Hamid Toranjzar, Javad Varvani, Nourollah Abdi

“…This study aims to evaluate the potential habitat of Astragalus sp. using three different species distribution modeling methods: the maximum entropy (MaxEnt) model, the Genetic Algorithm for Rule-Set Production (GARP), and logistic regression. …”
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A multi-objective path optimization method for plant protection robots based on improved A*-IWOA by Jing Niu, Chuanyan Shen, Lipeng Zhang, Qijun Li, Haohao Ma

“…Methods To address the challenges of achieving low energy consumption and efficiency in path planning for plant protection robots operating in mountainous environments, a multi-objective path optimization approach was developed. This approach combines the improved A* algorithm with the Improved Whale Optimization Algorithm (A*-IWOA), utilizing a 2.5D elevation grid map. …”
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SynthSecureNet: An Improved Deep Learning Architecture with Application to Intelligent Violence Detection by Ntandoyenkosi Zungu, Peter Olukanmi, Pitshou Bokoro

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Review on algorithms of dealing with depressions in grid DEM by Yi-Jie Wang, Cheng-Zhi Qin, A-Xing Zhu

“…Existing ways of improving the computation efficiency of depression-processing algorithms are also presented, i.e. serial algorithm optimization and parallel algorithms. …”
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YOLO-AMM: A Real-Time Classroom Behavior Detection Algorithm Based on Multi-Dimensional Feature Optimization by Yi Cao, Qian Cao, Chengshan Qian, Deji Chen

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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. …”
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Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network by Yansheng Huang, Atthapol Ngaopitakkul, Suntiti Yoomak

“…To solve the problem that traditional models tend to fall into locally optimal solutions (i.e., the model optimization process stays in the non-optimal regional minimum) in complex parameter space, the study innovatively proposes a hybrid prediction model that combines the whale optimization algorithm with the gated recurrent unit-long short-term memory neural network. …”
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Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization by Yuanwen Lai, Said Easa, Dazu Sun, Yian Wei

“…Accurate prediction can help passengers make travel plans and improve travel efficiency. Given the nonlinearity, randomness, and complexity of bus arrival time, this paper proposes the use of a wavelet neural network (WNN) model with an improved particle swarm optimization algorithm (IPSO) that replaces the gradient descent method. …”
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On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability by Tapasi Brahma, Alexander Guillen, Jeffrey Moreno, Abhishek Datta, Yu Huang

“…Material and method: Here we aim to study the inter-individual variability of optimized TI by applying the same optimization algorithms on N = 25 heads using their individualized head models. …”
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Coordinated optimal scheduling of island microgrid for power-hydrogen-carbon integration based on SAO-NSGA-II algorithm by XI Honglei, SUN Jingliao, QU Hezuo, SHI Zhengchai, HU Changhong, LIU Jinyuan

“…Finally， through simulation examples， a comparative analysis of the results before and after the algorithm improvement is performed， validating the feasibility of the proposed improved algorithm and optimal scheduling model. …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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Delay margin analysis of FOTID controller for RES based EV system using MMGPE optimization by Adhit Roy, Susanta Dutta, Soumen Biswas, Anagha Bhattacharya, Sajjan Kumar, Soham Dutta, Provas Kumar Roy

“…To do this, the current authors have created an asymptotic bode plot of a time-delayed FOTID controller and used rekasius substitution to calculate the delay margin (DM). Multi model multi-objective grey prediction evolution (MMGPE) optimization has been designed to fine-tune the previously specified controller settings. …”
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Passivity-Based Control for Rocket Launcher Position Servo System Based on ADRC Optimized by IPSO-BP Algorithm by Rong-lin Wang, Bao-chun Lu, Yuan-long Hou, Qiang Gao

“…Furthermore, to improve the learning capability, the improved PSO algorithm is adopted to optimize the learning rates of the back propagation neural networks. …”
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Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…In this study, we propose an evolutionary optimization strategy to enhance the accuracy and adaptability of RFC splines by optimizing their scaling factor and shape parameters using our novel Fractal Differential Evolution (FDE) algorithm. …”
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An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid by Yanming Cheng, Jinqi Zhang, Mahmoud Al Shurafa, Dejun Liu, Yulian Zhao, Chao Ding, Jing Niu

“…EMS is a control system integrated within MGs for managing the operations of these DGs effectively to fulfill a power balance between power production and load demand in the most optimal way, especially in island MGs. In this paper, an EMS based on Multiple Adaptive Neuro-Fuzzy Inference System optimized by Genetic Algorithm (MANFIS-GA) is proposed for PV/Wind/Diesel Generator/Battery (PWDB) island MG system, to optimize the output power of diesel generator, manage charging-discharging operation of MG Battery Storage keeping its State of Charge (SOC) in acceptable limits, and improve the MG system reliability and stability by mitigating the effects of sudden changes in the electrical loading and Renewable energy sources (RES) Power. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Evaluation and Improvement of Ocean Color Algorithms for Chlorophyll-<i>a</i> and Diffuse Attenuation Coefficients in the Arctic Shelf by Yubin Yao, Tao Li, Qing Xu, Xiaogang Xing, Xingyuan Zhu, Yubao Qiu

“…The proposed OCx-AS series for Chl-<i>a</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub></mrow></semantics></math></inline-formula>-DAS models for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> significantly reduce retrieval errors, achieving RMSE improvements of over 50% relative to global standard algorithms. …”
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