Design and Implementation of Hybrid GA-PSO-Based Harmonic Mitigation Technique for Modified Packed U-Cell Inverters by Hasan Iqbal, Arif Sarwat

“…This paper proposes a hybrid version of the GA-PSO algorithm that exploits the exploratory strengths of GA and the convergence efficiencies of PSO in determining the optimized switching angles for SHM techniques applied to modified five-level and seven-level PUC inverters. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

“…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
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Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. by Yeonuk Kim, Monica Garcia, T Andrew Black, Mark S Johnson

“…We found a strong correlation (r = 0.93) between the sensitivity of ET estimates to machine-learned parameters and model error (root-mean-square error; RMSE), indicating that reduced sensitivity minimizes error propagation and improves performance. …”
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AIBPO: Combine the Intrinsic Reward and Auxiliary Task for 3D Strategy Game by Huale Li, Rui Cao, Xuan Wang, Xiaohan Hou, Tao Qian, Fengwei Jia, Jiajia Zhang, Shuhan Qi

“…Finally, a framework of auxiliary intrinsic-based policy optimization (AIBPO) is proposed, which improves the performance of the IBPO. …”
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A Multi-Strategy ALNS for the VRP with Flexible Time Windows and Delivery Locations by Xiaomei Zhang, Xinchen Dai, Ping Lou, Jianmin Hu

“…In particular, the last-mile delivery is particularly important because it serves customers directly. Improving customer satisfaction is one of the important factors to ensure the quality of service in delivery and also an important guarantee for improving the market competitiveness of logistics enterprises. …”
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Degradation and reliability assessment of accuracy life of RV reducers by XU Hang, NIE Yixuan, WEN Dongjie, REN Jihua, HONG Zhihui

“…A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. …”
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Power Control for Full-Duplex Device-to-Device Underlaid Cellular Networks: A Stackelberg Game Approach by Zhen Yang, Titi Liu, Guobin Chen

“…The simulation results show that the proposed game algorithm improves network performance compared with other existing schemes.…”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…IntroductionMachine learning (ML) models have been increasingly applied to predict post-heart transplantation (HT) mortality, aiming to improve decision-making and optimize outcomes. …”
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Perimeter Degree Technique for the Reduction of Routing Congestion during Placement in Physical Design of VLSI Circuits by Kuruva Lakshmanna, Fahimuddin Shaik, Vinit Kumar Gunjan, Ninni Singh, Gautam Kumar, R. Mahammad Shafi

“…Consequently, in conjunction with the optimized floorplan data, the optimized model created by the Improved Harmonic Search Optimization algorithm undergoes testing and investigation in order to estimate the amount of congestion that occurs during the routing process in VLSI circuit design and to minimize the amount of congestion that occurs.…”
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High-Resolution and Robust One-Bit Direct-of-Arrival Estimation via Reweighted Atomic Norm Estimation by Rui Li, Jianchao Yang, Zheng Dai, Xingyu Lu, Ke Tan, Weimin Su

“…In recent years, one-bit quantization has attracted widespread attention in the field of direction-of-arrival (DOA) estimation as a low-cost and low-power solution. Many researchers have proposed various estimation algorithms for one-bit DOA estimation, among which atomic norm minimization algorithms exhibit particularly attractive performance as gridless estimation algorithms. …”
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Image Mosaic Based on Local Guidance and Dark Channel Prior by Chong Zhang, Fang Xu, Dejiang Wang, He Sun

“…Thirdly, the compensation of color and luminance difference of the overlap is applied to the overall image, which improves the inhomogeneity of stitching image. Eventually, the final result is obtained by enhancing algorithm based on dark channel prior. …”
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THEORETICAL AND METHODOLOGICAL PRINCIPLES OF APPLICATION OF AGENT-ORIENTED APPROACH TO MODELING PROCESSES OF LOCAL HROMADAS by Yevgen Kotukh, Maryna Riabokin

“…A proposed simulation framework combines the auction logic with reinforcement learning methods (MARL), where agents improve their strategies through interaction and feedback. …”
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Empc-based V2G scheduling strategy for multi-attribute EVs aggregator by Haoyang Tang, Zhilu Liu, Lin Zheng, Jianfeng Zheng, Hao Hu, Jinpei Lu, Zhijian Hu

“…The results show that compared with other strategies, the proposed EMPC algorithm can achieve 4–47.4 % reduction in charging costs, significantly reduce the peak valley difference and variance of load, and improve the load curve.…”
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Inversion and Fine Grading of Tidal Flat Soil Salinity Based on the CIWOABP Model by Jin Zhu, Shuowen Yang, Shuyan Li, Nan Zhou, Yi Shen, Jincheng Xing, Lixin Xu, Zhichao Hong, Yifei Yang

“…This study proposes an improved approach for soil salinity inversion in coastal tidal flats using Sentinel-2 imagery and a new enhanced chaotic mapping adaptive whale optimization neural network (CIWOABP) algorithm. …”
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Nonlinear Model Predictive Control for Trajectory Tracking of Omnidirectional Robot Using Resilient Propagation by Mahmoud El-Sayyah, Mohamad R. Saad, Maarouf Saad

“…This paper proposes an enhanced Nonlinear Model Predictive Control (NMPC) framework that incorporates a robust, convergent variant of the resilient propagation (RPROP) algorithm to efficiently solve the Nonlinear Optimization Problem (NOP) in real time. …”
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Deep neural network approach integrated with reinforcement learning for forecasting exchange rates using time series data and influential factors by T. Soni Madhulatha, Dr. Md. Atheeq Sultan Ghori

“…The algorithm leverages the strengths of both deep learning and reinforcement learning to achieve improved predictive accuracy and adaptability. …”
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Prediction of Carbonate Reservoir Porosity Based on CNN-BiLSTM-Transformer by Yingqiang Qi, Shuiliang Luo, Song Tang, Jifu Ruan, Da Gao, Qianqian Liu, Sheng Li

“…The model extracts curve features through the CNN layer, captures both short- and long-term neighborhood information via the BiLSTM layer, and utilizes the Transformer layer with a self-attention mechanism to focus on temporal information and input features, effectively capturing global dependencies. The Adam optimization algorithm is employed to update the network’s weights, and hyperparameters are adjusted based on feedback from network accuracy to achieve precise porosity prediction in highly heterogeneous carbonate reservoirs. …”
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High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics by Nauman Ahmed, Huigang Wang, Shanshan Tu, Norah A.M. Alsaif, Muhammad Asif Zahoor Raja, Muhammad Kashif, Ammar Armghan, Yasser S. Abdalla, Wasiq Ali, Farman Ali

“…For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. …”
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MC64-ClustalWP2: a highly-parallel hybrid strategy to align multiple sequences in many-core architectures. by David Díaz, Francisco J Esteban, Pilar Hernández, Juan Antonio Caballero, Antonio Guevara, Gabriel Dorado, Sergio Gálvez

“…The new parallelization approach has focused into the most time-consuming stages of this algorithm. In particular, the so-called progressive alignment has drastically improved the performance, due to a fine-grained approach where the forward and backward loops were unrolled and parallelized. …”
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