A Survey of Sampling Methods for Hyperspectral Remote Sensing: Addressing Bias Induced by Random Sampling by Kevin T. Decker, Brett J. Borghetti

“…In this work, we introduce a set of desirable characteristics to evaluate sampling algorithms, with a primary focus on their tendency to induce correlation between training and test data, while also accounting for other relevant factors. …”
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RLS adaptive filter co-design for de-noising ECG signal by Ahlam Fadhil Mahmood, Safaa N. Awny, Ali Alameer

“…The hardware component is responsible for creating a Finite Impulse Response (FIR) filter, while the adaptive processing is handled by the soft processor. …”
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Evolutionary Optimization for the Classification of Small Molecules Regulating the Circadian Rhythm Period: A Reliable Assessment by Antonio Arauzo-Azofra, Jose Molina-Baena, Maria Luque-Rodriguez

“…We applied a genetic algorithm to optimize feature selection and classification performance. …”
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Sensitivity analysis of activity scheduling parameters with a parameter optimization framework by Matheus Moro Zamprogno, Domokos Esztergár-Kiss

“…In this research, the activity chain optimization algorithm is applied, which requires high computational efforts. …”
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Analysis of Public Sentiment Towards POLRI's Performance using Naive Bayes and K-Nearest Neighbors by Yusuf Handika, Isa Faqihuddin Hanif, Firman Noor Hasan

“…The assessment from confusion matrix results demonstrate that the Naive Bayes algorithm achieves 99.03% accuracy, while the K-Nearest Neighbors algorithm achieves 95.33% accuracy. …”
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Using PAT for Energy Recovery and Pressure Reduction in Water Distribution Networks by Hamed Mohammadi, Mahnaz Ghaeini-Hessaroeyeh, Ehsan Fadaei-Kermani

“…Pressure reduction in water distribution networks is usually done using Pressure reducing valve (PRV), while the energy dissipated from head loss can be recovered to generate hydropower. …”
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An improvement in the design process of sustainable peak power rating transformer for solar utility by Emir Yükselen, Ebrahim Rahimpour

“…The transformer industry faces critical challenges, such as maintaining reliable production while meeting rising sustainability requirements. …”
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Version [2.0] - [VIC-Borg: Multiobjective automatic calibration toolkit for VIC model] by Jinfeng Ma, Hua Zheng, Ruonan Li, Kaifeng Rao, Yanzheng Yang, Weifeng Li

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Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based on Well Log Data by Urip Nurwijayanto Prabowo*, Akmal Ferdiyan, Sukmaji Anom Raharjo, Sehah Sehah, Arya Dwi Candra

“…The machine learning algorithm was carried out in 4 steps, i.e. data selection, training phase, verification, and validation stage. …”
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Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic by Bin Yang, Bin Song, Yadegar Abdi

“…Squeeze Net carefully learns complex data patterns to produce reliable predictions, while FCOA focuses on improving the prediction framework. …”
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Voltage control of floating interleaved boost converter using non-singular terminal sliding mode control algorithm for fuel cell systems by Bacha Khan Insafmal, Yanbo Che

“…The proposed dual loop cascade controller is utilizing a nonsingular terminal sliding mode control algorithm for voltage control in the outer loop and super twisting sliding mode control algorithm for current control in the inner loop. …”
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Comparative analysis of forest disturbance detection in the key state-owned forest region of the Greater Khingan Range of China based on different algorithms by Ke Xu, Wenshu Lin, Ning Zhang

“…Results showed that: (1) all three algorithms can identify the major forest disturbances with a spatial accuracy higher than 80%, and LandTrendr performed the best (OA=86.2%). (2) All three algorithms can detect the occurrence time of major disturbances with a temporal accuracy higher than 70%, and LandTrendr achieved the highest accuracy (76.4%). (3) The highest fragmentation was observed using the CCDC (184,074 disturbance patches), while LandTrendr disturbance mapping was the most complete (102,143 disturbance patches). …”
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Clinical and situational analysis structured elements of caries intensities in motivation of the algorithm’s rehabilitation of caries pathology beside flying personnel of civil avi... by G. G. Ashurov, M. K. Shokirov, G. E. Mullodzhanov, D. T. Makhmudov, M. R. Gurezov

“…Study the structured factors of caries intensities in depending of cariesology status’ level besides flying personnel of the civil aviation for the reason’s motivations of the algorithm to rehabilitations of caries pathology.MATERIALS AND METHODS. …”
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The Comparison Combination of Naïve Bayes Classification Algorithm with Fuzzy C-Means and K-Means for Determining Beef Cattle Quality in Semarang Regency by Feroza Rosalina Devi, Endang Sugiharti, Riza Arifudin

“…This can be seen from the combination accuracy of Fuzzy C-Means algorithm and Naïve Bayes Classifier of 96,67 while combination of K Means Clustering and Naïve Bayes Classifier algorithm is 98,33%, so it can be concluded that combination of K Means Clustering algorithm and Naïve Bayes Classifier is more recommended for determining the quality of beef cattle in Semarang regency.…”
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Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm by Yunfei Hu, Kefei Zhang, Sheng Liu, Zhong Wang

“…The optimization model aims to minimize system operating costs, carbon emissions, and thermal power output fluctuations, while maximizing the regulation flexibility of the VS-PS plant. …”
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Implementation of real-time optimal load scheduling for IoT-based intelligent smart energy management system using new decisive algorithm by Challa Krishna Rao, Sarat Kumar Sahoo, Franco Fernando Yanine

“…Experimental results demonstrate that the system effectively reduces overall energy consumption while maintaining user comfort and optimizing costs. …”
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Solving Spatial Optimization Problems via Lagrangian Relaxation and Automatic Gradient Computation by Zhen Lei, Ting L. Lei

“…Despite its merits, Lagrangian relaxation as a solution algorithm requires one to derive the (sub)gradients manually, which is error-prone and makes the solution algorithm difficult to develop and highly dependent on the model at hand. …”
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Semiparametric Transformation Models with a Change Point for Interval-Censored Failure Time Data by Junyao Ren, Shishun Zhao, Dianliang Deng, Tianshu You, Hui Huang

“…Model parameters are estimated via the EM algorithm, with the change point identified through a profile likelihood approach using grid search. …”
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GA-Attention-Fuzzy-Stock-Net: An optimized neuro-fuzzy system for stock market price prediction with genetic algorithm and attention mechanism by Burak Gülmez

“…The model's performance is evaluated across multiple temporal horizons using sliding windows (5-day, 10-day, 20-day) to capture varying market dynamics. Genetic algorithms optimize the hyperparameters, including learning rates and network architectures, while the attention mechanism enhances the model's ability to focus on relevant temporal patterns. …”
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A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning by Junyao Ding, Jianchao Du, Hejie Wang, Song Xiao

“…Then, the improved genetic algorithm is used to search for the global optimal feature subset further. …”
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