Optimizing Vehicle Routing for Perishable Products with Time Window Constraints: by Rifqi Fauzi, Adi Priansyah, Paskalis Krisna Puspadewa, Syifa Maulvi Zainun Awal, Huu Tho Nguyen, Achmad Pratama Rifai

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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

“…Next, sparse feature extraction is performed using Discrete Wavelet Transform (DWT), and a sparse matrix is constructed. A Genetic Algorithm (GA) is used to optimize the sparse matrix, which effectively selects the most significant features for prediction. …”
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AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…These limitations often lead to inefficiencies such as energy wastage, treatment delays, and overflow incidents, negatively impacting system performance and sustainability.AquaFlowNet leverages state-of-the-art machine learning algorithms to analyze real-time data from sensors, forecast flow variations, and optimize wastewater treatment processes. …”
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Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm by Elahe Akbari, Ali Darvishi Boloorani, Jochem Verrelst, Stefano Pignatti

“…Based on our proposed workflow in previous studies, a Gaussian process regression–particle swarm optimization (GPR-PSO) algorithm and global sensitivity analysis were applied to retrieve the fCover and biomass from Sentinel-2 satellite data and to identify the most sensitive parameters in the AquaCrop model, respectively. …”
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Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model by Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail

“…According to the experimental results, the proposed SSA-LSTM model has a more effective performance than the Support Vector Regression (SVR) method, the eXtreme Gradient Boosting (XGBoost) model, the traditional LSTM model, and the improved LSTM model with the Whale Optimization Algorithm (WOA-LSTM) in the passenger flow prediction. …”
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Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance by Velpuri Leela Devi, Piyush Kuchhal, Debasis de, Abhinav Sharma, Neeraj Kumar Shukla, Mona Aggarwal

“…In this research work, among those eight ML models, the XGBoost algorithm shows high accuracy for predicting the power conversion efficiency (PCE) of the cell, achieving root mean square error (RMSE) of 0.052 and a coefficient of determination (R2) of 0.999. …”
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Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique by Md Moktarul Alam, Richard Perdriau, Mohammed Ramdani, Mohsen Koohestani

“…This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. …”
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Multi-objective programming method for ship weather routing based on fusion of A* and NSGA-II by Yuankui LI, Jiyuan SUO, Dongye YU, Xinyu ZHANG, Fang YANG, Xuefeng YANG

“…ResultsThe simulation results demonstrate that the proposed model and algorithm can obtain a uniformly distributed and diversified Pareto optimal route set. …”
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Reinforcement learning algorithm for improving speed response of a five-phase permanent magnet synchronous motor based model predictive control. by Ahmed M Hassan, Jafar Ababneh, Hani Attar, Tamer Shamseldin, Ahmed Abdelbaset, Mohamed Eladly Metwally

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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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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms. By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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Control of a compliant gripper via least-squares support vector regression (LS-SVR) with particle swarm optimization (PSO) algorithm by Poonnapa Chaichudchaval, Archawin Chaitrekal, Nawin Sutthiprapa, Dung-An Wang, Teeranoot Chanthasopeephan

“…To address this, an algorithm developed to mitigate the effect of hysteresis is seen to improve control accuracy. …”
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Bus frequency optimization in a large-scale multi-modal transportation system: integrating 3D-MFD and dynamic traffic assignment by Kai Yuan, Dandan Cui, Jiancheng Long

“…However, as far as the authors know, most proposed bus frequency optimization formulations are based on static demand and the Bureau of Public Roads function, and do not properly consider the congestion dynamics and their impacts on mode choices. …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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Artificial Flora Algorithm-Based Feature Selection With Support Vector Machine for Cardiovascular Disease Classification by M. M. Asha, G. Ramya

“…This approach utilizes the Cleveland dataset by combining the Artificial Flora Optimization algorithm with the Support Vector Machine. …”
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Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 by Riya Karmakar, Sandip Chatterjee, Debabrata Datta, Dipankar Chakraborty

“…In this paper, a music-inspired metaheuristic optimization algorithm, named Harmony Search (HS), has been integrated with ARIMA in order to improve the forecasting of the COVID-19 data set. …”
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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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Arithmetic coder optimization for compressing images obtained through remote probing of water bodies by R. V. Arzumanyan

“…In the course of work, the most computationally complex parts of the arithmetic coder algorithm are determined. …”
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