Research on Denoising of Bridge Dynamic Load Signal Based on Hippopotamus Optimization Algorithm–Variational Mode Decomposition–Singular Spectrum Analysis Method by Zhengqiang Zhong, Zhen Li, Jinlong Wang, Cong Tang, Yu Liu, Kaijun Guo

“…To address this issue, this research proposes a denoising method that combines the hippopotamus optimization algorithm (HOA), variational mode decomposition (VMD), and singular spectrum analysis (SSA). …”
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Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Farshad Ahmadi, Rasoul Mirabbasi, Ali Torabi Haghighi

“…In this study, a novel innovative deep neural network (DNN) structure by integrating a double Gated Recurrent Units (GRU) neural network model with a multiplication layer and meta-heuristic whale optimization algorithm (WOA) (i.e., hybrid 2GRU×–WOA model) is developed to improve the prediction accuracy and performance of mean monthly Chehel-Chai River’s streamflow (CCRSF m ) in Iran. …”
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Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area by M. Sofiya, M. Arulmozhi

“…The Exhaustive Traffic Information Rate (ETIR) method evaluates the marginal rate of each feature, and the AntLion Behavior Optimization (ALBO) algorithm selects the most significant features, reducing dimensionality. …”
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Noise Processing Method of MEMS Tilt Sensor Using Improved Kalman Filter Based on Quantum Particle Swarm Optimization by Yutong Ge, Weizheng Ren, Kaile Yu, Yiran Zhang, Yuxiao Li

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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin Ab Rahman, Sakib Iqram Hamim

“…However, due to the limited battery capacity of sensor nodes, energy efficiency remains a critical challenge, especially since data transmission consumes the most energy. This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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Machine Learning Performance Analysis for Bagging System Improvement: Key Factors, Model Optimization, and Loss Reduction in the Fertilizer Industry by Ari Primantara, Udisubakti Ciptomulyono, Berlian Al Kindhi

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Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking by Athanasios Sidiropoulos, Dimitrios Bechtsis, Dimitrios Vlachos

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Improvement of the Dynamic Response of Robust Sliding Mode MPPT Controller-Based PSO Algorithm for PV Systems under Fast-Changing Atmospheric Conditions by Dieudonné Marcel Djanssou, Abdouramani Dadjé, Ahmat Tom, Noël Djongyang

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A Novel Back Propagation Neural Network Based on the Harris Hawks Optimization Algorithm for the Remaining Useful Life Prediction of Lithium-Ion Batteries by Yuyang Zhou, Zijian Shao, Huanhuan Li, Jing Chen, Haohan Sun, Yaping Wang, Nan Wang, Lei Pei, Zhen Wang, Houzhong Zhang, Chaochun Yuan

“…In order to achieve accurate and reliable RUL prediction, a novel RUL prediction method which employs a back propagation (BP) neural network based on the Harris Hawks optimization (HHO) algorithm is proposed. This method optimizes the BP parameters using the improved HHO algorithm. …”
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Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing by Aminu Aminu Muazu, Ahmad Sobri Hashim

“…Optimization has developed powerful algorithms for solving complex problems efficiently. …”
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Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs by Umair B. Chaudhry, Chris Ian Phillips

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Financial Market Evaluation Utilizing an Optimized Deep-Learning Model: A Case Study of the Nikkei 225 by Karthikeyan M P

“…The precision of the stock market forecasts can be improved using metaheuristic algorithms such as the Moth-flame optimizer, which will provide the best optimization of the hyperparameters for an LSTM model. …”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…We also improved several resampling strategies, such as undersampling and oversampling. …”
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GA4RF: An Effective Fall Detection System Through Optimizing Random Forest Hyperparameters Using Genetic Algorithm With Mobile Sensor Data by Ha-Nam Nguyen, Hong-Lam Le, Ngo-Thi-Thu-Trang, Duc-Nhan Nguyen

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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

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Association Analysis of Benzo[<i>a</i>]pyrene Concentration Using an Association Rule Algorithm by Minyi Wang, Takayuki Kameda

“…Herein, the factors influencing B(a)P concentration were elucidated by analyzing the monthly environmental data for Kyoto, Japan, from 2001 to 2021 using an improved association rule algorithm. Results revealed that B(a)P concentrations were 1.3–3 times higher in cold seasons than in warm seasons and SPM concentrations were lower in cold seasons. …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Abstract The purpose of this study was to model and optimize the removal of methylene blue using a novel magnetic chitosan-carboxymethyl cellulose/multiwalled carbon nanotubes and to identify the most significant parameters influencing the adsorption efficiency. …”
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Landing scheduling for carrier aircraft fleet considering bolting probability and aerial refueling by Genlai Zhang, Lei Wang, Zhilong Deng, Xuanbo Liu, Xichao Su, Haixu Li, Chen Lu, Kai Liu, Xinwei Wang

“…Aiming at an efficient solution, an improved firefly algorithm is designed by integrating multiple evolutionary operators. …”
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Optimization of the flow guiding fins configuration and tube arrangements in a shell and tube heat exchanger: coupling response surface methodology and CFD by Xiangmin Shao, Ali Marzban, Farzad Pourfattah, Omid Ali Akbari, Gholamreza Ahmadi, Nafiseh Emami, Soheil Salahshour

“…The simulation results of the two-phase flow of water-MWCNT nanofluid in the optimal arrangement of conducting fins show that the heat transfer is improved and the coefficient of performance is greater than 1.…”
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Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis by Rihab Lakbichi, Farouq Zitouni, Saad Harous, Aridj Ferhat, Abdelhadi Limane, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…In recent years, opposition-based learning (OBL) has emerged as a powerful enhancement strategy in metaheuristic algorithms (MAs), gaining significant attention for its potential to accelerate convergence and improve solution quality. …”
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