An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

“…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability a... by Fude Duan, Ali Basem, Dheyaa J. Jasim, Mahdiyeh Eslami, Mustafa Okati

“…The Multi-Objective Improved Horse Herd Optimizer (MOIHHO) is derived from an enhanced version of the traditional horse herd optimizer. …”
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A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization by Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu

“…To handle this difficulty, a novel fault signal denoising scheme based on improved sparse regularization via convex optimization is proposed to extract the fault feature of rolling bearing. …”
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A data-driven cost estimation model for agile development based on Kolmogorov-Arnold Networks and AdamW optimization by Xiaoyan Zhao, Xin Xiong, Zulkefli Mansor, Rozilawati Razali, Mohd Zakree Ahmad Nazri, Liangyu Li

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Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection by R. Sudha, Ajith Damodaran, Gunaselvi Manohar

“…The proposed model introduces a novel methodology for weighted feature selection utilizing an Improved Gannet Optimization Algorithm (IGOA) aimed at enhancing the performance of data classification. …”
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Multi-strategy improved runge kutta optimizer and its promise to estimate the model parameters of solar photovoltaic modules by Serdar Ekinci, Rizk M. Rizk-Allah, Davut Izci, Emre Çelik

“…In our endeavor, we introduce a multi-strategy improvement approach for the Runge Kutta (RUN) optimizer, a cutting-edge tool used for tackling this critical task in both single-diode and double-diode PV unit models. …”
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Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

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Evolutionary Cost Analysis and Computational Intelligence for Energy Efficiency in Internet of Things-Enabled Smart Cities: Multi-Sensor Data Fusion and Resilience to Link and Devi... by Khalid A. Darabkh, Muna Al-Akhras

“…Thorough simulations and comparative analysis reveal the protocol’s superior performance across key performance metrics, namely, network lifespan, energy consumption, throughput, and average delay. When compared to the most recent and relevant protocols, including the Particle Swarm Optimization-based energy-efficient clustering protocol (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), and Novel PSO-based Protocol (NPSOP), our approach achieves very promising results. …”
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Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

“…To further improve feature selection, we utilize the Chaotic Whale Optimization (ChWO) Algorithm, which optimally selects the most relevant attributes from the extracted features. …”
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A Study on the Design of a New Three-Dimensional Seismic Isolation Bearing Based on an Improved Genetic Algorithm for Bridge Engineering by Ying Sheng, Zhenchao Yang, Yu Meng, Bin Jia

“…However, passive seismic isolation devices, due to their non-adjustable performance parameters, struggle to achieve effective seismic isolation across a wide frequency range of 0 Hz to 20 Hz in response to random and varying seismic loads. (2) Methods: The sensitivity of the design parameters of the seismic isolation bearing was analyzed using the optimization center gradient method, and an improved genetic algorithm was employed to quickly optimize and obtain the optimal design parameters. (3) Results: The effectiveness of the three-dimensional seismic isolation bearing was validated through experiments. (4) Conclusions: The multi-factor sensitivity analysis approach used in this study for designing novel isolation bearings is applicable not only to seismic design in bridges but also serves as a reference for parameter design in isolation bearings requiring medium to high precision in seismic performance.…”
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Hybrid RSA-ROA Scheduling Algorithm for Minimization of Power Loss and Improving the Renewable with Sustainable Energy Harvesting in Power System by Cuddapah Anitha, Virendra Swaroop Sangtani, Ajay Kumar Bansal, Mahaveerakannan R., R. Rajesh Sharma, Saravanan M. S.

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Remaining useful life prediction of a small sample of aero-engine based on an improved gray Markov model by Dong-hai Li, Ji-liang Tu, Hui Liu, Nai-zhi Liao

“…To enhance adaptability, a genetic algorithm dynamically optimizes the time response parameters of the grey model, overcoming the limitation of a fixed structure in traditional methods. …”
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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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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…To address the issue of rolling bearing fault diagnosis, this paper proposes a novel model combining the Improved Gorilla Troop Optimization (IGTO) algorithm, Variational Mode Decomposition (VMD), Permutation Entropy (PE), and Long Short-Term Memory (LSTM) networks. …”
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Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

“…The goals of this study were to (i) identify optimal spectral indices and texture features from RGB and multispectral (MS) images and (ii) improve the accuracy of PNC prediction by combining optimal features with ML. …”
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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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An Investigation into the Rescue-Path Planning Algorithm for Multiple Mine Rescue Teams Based on FA-MDPSO and an Improved Force-Directed Layout by Qiangyu Zheng, Peijiang Ding, Zhixin Qin, Zhenguo Yan

“…Subsequently, the hyperparameters of MDPSO (Multiple Constraints Discrete Particle Swarm Optimisation) were optimised by means of four intelligent algorithms—ACO (Ant Colony Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and WOA (Whale Optimization Algorithm). …”
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Energy-environment-economic study and optimization: An advanced heat recovery method for improving gas turbine cycle efficiency by Chaoxin Ji, Azher M. Abed, Xiao Zhou, Guoliang Lei, Li He, T.H. AlAbdulaal, Barno Abdullaeva, Mohammad Sediq Safi

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An improved hybrid artificial bee colony algorithm for a multi-supplier closed-loop location inventory problem with customer returns. by Hao Guo, Xiaomei Lai, Ju Guo, Ge You, Ibrahim Alnafrah

“…The objective of the CLLIP is to minimize overall supply chain costs by optimizing facility location and inventory management strategies. …”
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PSO Based Optimization of Testing and Maintenance Cost in NPPs by Qiang Chou, Daochuan Ge, Ruoxing Zhang

“…In this paper, we adopt PSO as an optimizer to optimize the multiobjective optimization problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. …”
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