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

Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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). …”
Get full text

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. …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Investigation of the Effect of Upstream Slope and Bed Material on the Rate of Pollutant Release to Downstream Dams Using a Two-Phase SPH algorithm by Rahim Shamsoddini, Bahador Abolpour, Yi Zhao

Get full text

Replacing Backpropagation with the Forward-Forward (FF) Algorithm in Transformer Models: A Theoretical and Empirical Study on Scalable and Efficient Gradient-Free Training by Hyun Jung Kim, Sang Hyun Yoo

“…This study proposes a novel integration of the Forward-Forward (FF) algorithm into Transformer architectures as an efficient and gradient-free alternative to Backpropagation (BP). …”
Get full text

A Tuning Method for Speed Tracking Controller Parameters of Autonomous Vehicles by Jianqiao Chen, Guofu Tian

“…This paper addresses the challenge of speed tracking by proposing a genetic algorithm-based optimization method for PID controller parameters. …”
Get full text

Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

“…To classify the ripe and unripe pistachios with a small-sized and high test accuracy model, a two-layer CNN architecture’s hyperparameters were optimized with the proposed algorithm. The implementation of the proposed algorithm took 14 hours and 17 minutes, and the algorithm calculated 173 different CNN architectures with different parameters. …”
Get full text

Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning by Mu Chen, Yong Li, Nige Li, Yinan Zhong, Guangxin Guo

Get full text

Optimization of a macro-algae-based biodiesel supply chain: a multi-objective approach by Prajwal Panwar, Anubhav Pratap Singh, Anand Chauhan, Ritu Arora

“…The main contribution lies in developing a multi-objective optimization model that minimizes supply chain costs and environmental impacts while addressing critical factors such as transportation logistics, facility placement and the impact of advertising on biodiesel demand. …”
Get full text

A voice-based algorithm can predict type 2 diabetes status in USA adults: Findings from the Colive Voice study. by Abir Elbéji, Mégane Pizzimenti, Gloria Aguayo, Aurélie Fischer, Hanin Ayadi, Franck Mauvais-Jarvis, Jean-Pierre Riveline, Vladimir Despotovic, Guy Fagherazzi

“…This study investigates the potential of using a voice-based algorithm to predict T2D status in adults, as the first step towards developing a non-invasive and scalable screening method. …”
Get full text