Predicting Irrigation Water Quality Indices Based on Data-Driven Algorithms: Case Study in Semiarid Environment by Dimple Dimple, Jitendra Rajput, Nadhir Al-Ansari, Ahmed Elbeltagi

“…The KR and SAR values were predicted accurately by the SVM model in comparison to the observed values. As a result, machine learning algorithms can improve irrigation water quality characteristics, which is critical for farmers and crop management in various irrigation procedures. …”
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Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

“…The primary objective of this system is to efficiently classify and analyze social media content related to Hajj and Umrah services. To improve the effectiveness of this classification model, we introduce a predictive optimization strategy that employs a deep neural network as the learning module and utilizes particle swarm optimization to refine the weighting parameters. …”
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A device free high-precision indoor positioning and tracking method based on GMM-WKNN algorithm by Mumen Jiang, Jiangnan Yuan

“…Abstract To address the high deployment complexity and algorithmic intricacies associated with current indoor target localization and tracking methods, this paper presents a Wi-Fi CSI indoor localization and tracking algorithm that integrates a Gaussian Mixture Model (GMM) with Weighted K-Nearest Neighbors (WKNN) and Kalman filtering. …”
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A two phase differential evolution algorithm with perturbation and covariance matrix for PEMFC parameter estimation challenges by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe

“…These numerical results emphasize PCM-DE’s ability to outperform existing algorithms in accuracy, convergence speed, and consistency, showcasing its potential for advancing PEMFC modeling and optimization. …”
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Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…To illustrate the application of these novel indices, we introduce an improved version of the dynamic fuzzy c-means algorithm (I-DFCM) which offers enhanced computational stability for handling dynamic data. …”
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Multi-service differentiated traffic management optimization strategy in cloud data center by Yaomin WANG, Xia WANG, Yi DONG, Lian GAO, Songhai ZHANG, Xinling SHI

“…In order to cope with the traffic management for multi-service differentiated in cloud data centers,improving network performance and service experience,the multi-service differentiated (MSD) traffic management model was designed that can suit operational requirements in cloud data center.Fibonacci tree optimization (FTO) algorithm was improved according to the MSD model.MSD-FTO traffic management strategy was proposed in SDN cloud data center.Simulation results show that the strategy takes advantage of FTO global optimization ability and multi-modal adaptive performance.Through the global local alternating optimization of the algorithm,differentiation traffic management schemes are obtained as needed,the problem of multi-services differentiated traffic management is solved in operator cloud data center that improve network performance and service experience in cloud data center effectively.…”
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Kinematic Constrained RRT Algorithm with Post Waypoint Shift for the Shortest Path Planning of Wheeled Mobile Robots by Sisi Liu, Zhan Zhao, Jun Wei, Qianqian Zhou

“…Once the distance between the new node and the target is within a certain threshold, the tree growth stops and a target connection based on minimum turning radius arc is proposed to generate an initial complete random path. The most significant difference from traditional RRT-based methods is that the proposed method optimizes the path based on Dubins curves through a post waypoint shift after a random path is generated, rather than through parent node selection and rewiring during the exploring tree growth. …”
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Research of Speech Recognition Algorithm Based on Time Delay Neural Network and Its Application in Rail Transit by LIU Yue, LIN Jun, LUO Xiao, CHU Wei, LIU Ren

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Prediction of effective moment of inertia for hybrid FRP-steel reinforced concrete beams using the genetic algorithm by A. Kheyroddin, F. Maleki

“…In this paper, we proposed a new equation for estimating the effective moment of inertia of hybrid FRP-steel reinforced concrete (RC) beams on the basis of the genetic algorithm and experimental results.The genetic algorithm is used to optimize the percent error between experimental and analytical responses. …”
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Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

“…To address these issues, appropriate parameters are needed in the Backpropagation training process, such as an optimal learning function. The aim of this study is to evaluate and compare various learning functions within the Backpropagation algorithm to determine the best one for prediction cases. …”
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An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior. by Fanlong Zeng, Jintao Wang, Chaoyan Zeng

“…The framework integrates an Improved Hunter-Prey Optimization (IHPO) algorithm, an eXtreme Gradient Boosting (XGBoost) model, and SHapley Additive exPlanations (SHAP) theory to predict and interpret corporate ESG greenwashing behavior. …”
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Fluid–Structure Interaction Study in Unconventional Energy Horizontal Wells Driven by Recursive Algorithm and MPS Method by Xikun Gao, Dajun Zhao, Yi Zhang, Yong Chen, Zhanzhao Gao, Xiaojiao Zhang, Shengda Wang

“…This study presents a novel bidirectional fluid–structure interaction (FSI) model, uniquely integrating recursive algorithms with the Moving Particle Semi-implicit (MPS) method to couple drill string–wellbore contact with drilling fluid interactions. …”
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Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning by Yinglei Li, Qingping Hu, Shiyan Sun, Wenjian Ying, Xiaojia Yan

“…This study proposes an error allocation method based on the improved raccoon optimization algorithm (KYCOA) to resolve the problem of degradation of positioning accuracy due to multi-source error coupling during UAV target positioning. …”
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Optimization of particle swarm for force uniformity of personalized 3D printed insoles by Zhao Jiali, Liu Jinhai, Liu Yuan

“…This research proposes an optimization model that combines the PSO algorithm with a variable density algorithm, enabling dynamic adjustments to the support capabilities of different regions of the insole to achieve uniform force distribution. …”
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INFO-RF-based fault diagnosis and analysis method for busbars by Chen Xue, Jian Zhu, Haiou Cao, Yan Gu, Siyu Chen

“…The RF model is then used to predict fault types and fault resistance, with the INFO algorithm iteratively optimizing the hyperparameters of the RF model to further improve prediction accuracy. …”
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Aerodynamic Parameter Identification of Projectile Based on Improved Extreme Learning Machine and Ensemble Learning Theory by Tianyi Wang, Wenjun Yi, Youran Xia

“…The improved particle swarm optimization algorithm (IPSO) with an adaptive update strategy is used to optimize the weight and threshold of ELM. …”
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A state evaluation and fault diagnosis strategy for substation relay protection system integrating multiple intelligent algorithms by Jiajun Wang, Shiyi Jing, Yu Yao, Kunlun Wang, Bo Li

“…This study introduces a new diagnostic framework that combines improved particle swarm optimization, K‐means clustering algorithms, support vector machine (SVM), and learning vector quantization neural networks to provide a comprehensive fault diagnosis and prediction model for relay protection systems. …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…Simulation results are then propagated into MOBO to generate Pareto-optimal solutions of the objective functions. A sensitivity analysis was conducted to tune the hyperparameters of the MOBO algorithm, including the covariance kernel of the surrogate model. …”
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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…The proposed WCAPSO-XGB model tunes the hyperparameters of XGBoost and classifies the credit scoring, and the experimental results are compared with various classifier such as Random Forest (RF), K-neighbors (KNN), Gaussian Naive Bayes (NB), AdaBoost, Gradient Boosting, Logistic Regression (LR), Neural Network (NN), Decision Tree (DT) and Linear Discriminant Analysis (LDA), and hyperparameter optimization methods, such as Grid Search (GS), Random Search (RS), Bays Optimization, Optuna Optimization, Hybrid Snake Optimizer Algorithm (HSOA), Exploratory Cuckoo Search, island Cuckoo Search (iCSPM and iCSPM2), and Improved SSA (ISSA) with HDPM, on four different datasets with a varying number of instances from small to large. …”
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Dynamic economic emission dispatch of combined heat and power system based on multi-objective differential evolution algorithm. by Tao Dong

“…Based on this algorithm, the dynamic economic emission dispatch model of combined heat and power system is constructed to optimize the economic and environmental benefits of the system. …”
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