Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems by Amirhossein Hamzeiyan, Armin Ebrahimi

“…These scenarios were designed to explore the algorithm's adaptability to different operating conditions and to evaluate its effectiveness across varying system constraints. …”
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Comparing supervised classification algorithm–feature combinations for Spartina alterniflora extraction: a case study in Zhanjiang, China by Qiujie Chen, Qiujie Chen, Chunyan Shen, Hong Du, Danling Tang

“…According to visual interpretation, the area of S. alterniflora increased by 3.35 ha over a 5-year period, indicating a growth rate of 5.13%. By evaluating the accuracy of different classification methods and features, this research can facilitate S. alterniflora extraction and provide support for mangrove conservation efforts.…”
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Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology. by Yu Cai, Xi-Ru Huang, Sheng-Jia Wang, Ying-Chao Liang, De-Liang Liu, Shu-Fang Chu, Hui-Lin Li

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Application of Machine Learning to Statistical Evaluation of Artificial Rainfall Enhancement by Li Dan, Lin Wen, Liu Qun, Feng Hongfang, Hu Shuping, Wang Zhihai

“…Different historical regression statistical test schemes of rainfall enhancement effects are compared and analyzed, aiming to further optimize the best natural rainfall estimation algorithm based on alterable contrast area with statistical method, which can provide reference for the assessment of artificial rainfall enhancement effects. …”
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Application of Machine Learning Algorithms for Predicting the Dynamic Stiffness of Rail Pads Based on Static Stiffness and Operating Conditions by Isaac Rivas, Jose A. Sainz-Aja, Diego Ferreño, Víctor Calzada, Isidro Carrascal, Jose Casado, Soraya Diego

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A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes by Shuheng Yang, Ralf Weiskirchen, Wenjing Zheng, Xiangxu Hu, Aibiao Zou, Zhiguo Liu, Hualin Wang

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Evaluating the Stability of Numerical Schemes for Fluid Solvers in Game Technology by Craig R. Stark, Declan A. Diver

“…To exemplify the method to evaluate numerical stability, a range of finite difference schemes is considered. …”
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Correlation coefficients of vibration signals and machine learning algorithm for structural damage assessment in beams under moving load by Toan Pham-Bao, Vien Le-Ngoc

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Information Diffusion Interpolation Model Based on the PSO-CV Algorithm and Its Application on Source Regions of the Yellow River by HUANG Huaping, YIN Kaixia, JIN Gaoyang

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A Linear Regression Prediction-Based Dynamic Multi-Objective Evolutionary Algorithm with Correlations of Pareto Front Points by Junxia Ma, Yongxuan Sang, Yaoli Xu, Bo Wang

“…The Dynamic Multi-Objective Evolutionary Algorithm (DMOEA) is an effective way for solving DMOPs. …”
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Resolution enhanced sea ice concentration: a new algorithm applied to AMSR2 microwave radiometry data by Jozef Rusin, Thomas Lavergne, Anthony P. Doulgeris, K. Andrea Scott

“…Passive-microwave sea ice concentration (SIC) algorithms employ different frequencies and polarisations in their operational implementations. …”
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Dynamical analysis of fractional hepatitis B model with Gaussian uncertainties using extended residual power series algorithm by Qursam Fatima, Mubashir Qayyum, Murad Khan Hassani, Ali Akgül

“…The robustness of the model is further evaluated using r-cut values for lower and upper bounds.A graphical analysis is also performed to examine the influence of different parameters on the solution profiles, enhancing the understanding of disease dynamics. …”
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SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS by V. M. Deundyak, M. A. Zhdanova

“…The solution is based on Shun-Zheng Yu forward algorithm for a general hidden semi-Markov model. This approach differs from the traditional one and employs posterior probabilities. …”
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Predicting Diabetes Mellitus with Machine Learning Techniques by Heba Ahmed Jassim, Omar R. Kadhim, Zahraa Khduair Taha, Johnny Koh Siaw Paw, Yaw Chong Tak, Tiong Sieh Kiong

“…The Diabetes Prediction Dataset is used to evaluate four machine learning algorithms. The classifier that deserves a singular mention is the Artificial Neural Network (ANN), which achieves a 97% accuracy rate. …”
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Detecting Anomalies in CPU Behavior Using Clustering Algorithms from the Scikit-Learn Library in Python Programming Language by Artem Turashev, Vladimir Sukhomlin

“…Experiments are conducted on real data obtained from CPU monitoring systems to evaluate the performance and compare the results of different algorithms. …”
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A novel deep reinforcement learning‐based algorithm for multi‐objective energy‐efficient flow‐shop scheduling by Peng Liang, Pengfei Xiao, Zeya Li, Min Luo, Chaoyong Zhang

“…Abstract A novel algorithm combining bidirectional recurrent neural networks (BiRNNs) with temporal difference is proposed for multi‐objective energy‐efficient non‐permutation flow‐shop scheduling problem (NFSP). …”
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NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families. by Hyun-Myung Woo, Hyundoo Jeong, Byung-Jun Yoon

“…A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. …”
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Hybrid signal algorithm detection in NOMA 5G waveform: Transforming smart healthcare connectivity by reducing latency by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…For 16 × 16 and 64 × 64 MIMO-NOMA, the Bit error rate (BER) was evaluated and compared for Long Short-Term Memory (LSTM), ZFE, MMSE, and Maximum likelihood (ML) detection, and the proposed ZFE-MMSE algorithms. …”
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A Modified Sine Cosine Algorithm Based on A Novel Locally Weighted Method for Global Optimization Problems by Shahad Mohammed, Nazar Hussein, Mohammed Alkahya

“…The putative method's hybrid architecture is anticipated to significantly increase the potential for exploration and exploitation. By evaluating SCA's performance against IEEE CEC 2017 functions and contrasting it with a variety of different metaheuristic techniques, the usefulness of SCA is investigated. …”
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Performance improvement of DC motor control system using PID controller with Kookaburra and Red Panda optimization algorithm by G. Saravanan, C. Pazhanimuthu, Palanichamy Naveen

“…The better solution of the algorithm is evaluated in the exploration and exploitation phases of the initial population in the metaheuristic algorithms. …”
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