Research on Gearbox Fault Diagnosis based on Improved LMD Algorithm by Haibo Xing, Yue Chen, Jinghao Li

“…Aiming at the fault diagnosis of gearbox，an Improved Local Mean Decomposition （ILMD） algorithm is proposed and applied to the extraction of fault features of gearbox. …”
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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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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. …”
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Optimization Design of Flexible Net Capture System for Low, Slow, and Small Unmanned Aerial Vehicles Based on Improved Multi-Objective Wolf Pack Algorithm by Ran Xu, Qiang Peng, Husheng Wu

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Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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Application of Optimization Algorithms in Voter Service Module Allocation by Edgar Jardón, Marcelo Romero, José-Raymundo Marcial-Romero

“…Six heuristics were analyzed in sequence: genetic algorithm, ant colony optimization, local search, tabu search, simulated annealing, and greedy algorithm. …”
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An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy by Dingya CHEN, Hui LIU, Yanfei LI, Zhu DUAN

“…Finally, the high frequency component is decomposed secondarily using variational mode decomposition optimized by beluga whale optimization algorithm. In the deep learning prediction stage, a deep extreme learning machine optimized by the sparrow search algorithm was used to obtain the prediction results of all subseries and reconstructs them to obtain the final soybean future price prediction results. …”
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A Hybrid Optimization Approach for Improving Sensor Configuration to Enhance Nasogastric Tube (NGT) Localization During Insertion and Withdrawal by M. Souganttika, Shaohui Foong

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Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem by Huthaifa Al-Khazraji

“…The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. …”
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Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm by Wenliang Zhu, Guanming Qiu

“…Addressing issues such as pronounced randomness, low search efficiency, inefficient utilization of effective points, suboptimal path smoothness, and potential deviations from the optimal path in the RRT algorithm based on random sampling, we proposed an optimization algorithm that integrates Kalman filtering to eliminate redundant points along the path. …”
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Multi-clustering algorithm based on improved tensor chain decomposition by ZHANG Hongjun, ZHANG Zeyu, ZHANG Yingjiao, YE Hao, PAN Gaojun

“…The innovations were mainly reflected in two aspects: firstly, a new tensor decomposition framework was proposed, which effectively reduced the storage cost and improved the computational efficiency by optimizing the objective function; secondly, the improved tensor decomposition technique was applied to three main multi-clustering algorithms, including self-weighted multi-view clustering (SwMC), latent multi-view subspace clustering (LMSC), and multi-view subspace clustering with intactness-aware similarity (MSC IAS), which significantly improved the accuracy and efficiency of clustering. …”
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Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment by Xun Lu, Junlei Liu, Xinmiao Liu, Jun Liu, Lingxue Lin

“…The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. …”
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Multiscale feature tuned trans-DeepLabV3+ based semantic segmentation of aerial images using improved red piranha optimization algorithm by P. Anilkumar, K. Lokesh, A. Naveen Kumar, D. John Pradeep, Y. V. Pavan Kumar, Rammohan Mallipeddi

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An Improved SLIC Superpixel Segmentation Algorithm Combined with FPGA Technology by HAN Jianhui, LZhi qiang

“…In view of the large amount of calculations, complexity of algorithm and the implementation is slow The paper combines superpixel segmentation technology with FPGA parallel processing technology, and puts forward a method to realize the image segmentation algorithm on FPGA platform SLIC is a kind of fast image segmentation algorithm SLIC has a lot of improvements in efficiency, costing and segmentation results compared with traditional image segmentation algorithm On the basis of the principle of SLIC segmentation algorithm, we made a further improvement algorithm by optimizing the operation and extracting a small number of pixels of the original image to reduce computational complexity Finally, the last of the original image segmentation was achieved by K nearest neighbor classification process We completed the algorithm design on FPGA platform The simulation results show that the improved algorithm has a better segmentation results and the processing speed has about 40% promotion And the improved algorithm has a higher realtime performance…”
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Improving Trajectory Tracking of Differential Wheeled Mobile Robots With Enhanced GWO-Optimized Back-Stepping and FOPID Controllers by Li Qiang, Hooi Hung Tang, Nur Syazreen Ahmad

“…Simulations demonstrate the superior performance of the proposed GWO-SMA algorithm compared to existing optimization techniques, such as Particle Swarm Optimization (PSO), Gazelle Optimization Algorithm (GOA), and its individual components, GWO and SMA, which have shown strong performance in recent literature for optimizing PID-type controllers. …”
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Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith... by Mojgan Bordbar, Khabat Khosravi, Changhyun Jun, Dongkyun Kim, Sayed M Bateni, Mahmood Safarzadeh, Hamid Kardan Moghaddam, Shohreh Azizi

“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
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An optimal design method of the resonant-free C-type filter by XU Fangwei, JIA Junwei, GUO Kai, XU Lin, CHEN Jiale, LU Yuguo

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System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario by Wenhao Luo, Yuan Zeng, Ximeng Zheng, Lingyan Zha, Weicheng Cai, Qing Wang, Jingjin Zhang

“…Finally, a network coverage optimization scheme was designed by combining a particle swarm optimization (PSO) algorithm and link quality prediction model, and a reliable cluster routing protocol was designed by combining K-means algorithm. …”
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Improving frequency stability in grid-forming inverters with adaptive model predictive control and novel COA-jDE optimized reinforcement learning by Muhammad Zubair Yameen, Zhigang Lu, Fayez F. M. El-Sousy, Waqar Younis, Baqar Ali Zardari, Abdul Khalique Junejo

“…The offline phase employs a novel Hybrid Crayfish Optimization and Self-Adaptive Differential Evolution Algorithm (COA-jDE) to minimize the cost function $$U_{offline}$$ , deriving optimal control parameters (Q, R) before real-time deployment. …”
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Model of Effective Business Formation by V. G. Khalin, G. V. Chernova, S. A. Kalayda

“…The task of improving business performance always raises the problem of choosing the most effective ways to ensure it. …”
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