Development of an Optimized Ensemble Least Squares Model for Identifying Potential Deposit Customers by Firman Aziz, Mutia Maulida, Jafar Jafar, Nurafni Shahnyb, Norma Nasir, Ampauleng Ampauleng

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Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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A hybrid ultra-short-term photovoltaic power prediction framework integrating ant colony optimization for clustering with Bi-GRU by Xinyi Liu, Zitao Wang, Yang Wang, Shanke Liu, Lijun Yu

“…This hybrid framework employs an improved Ant Colony Optimization algorithm fused with K-Means pre-clustering (K-MACO) to perform unsupervised learning on samples within the physical feature space of radiation patterns, humidity, and temperature dynamics, classifying weather scenarios into sunny, cloudy, and rainy types. …”
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Frequency Dependent Spencer Modeling of Magnetorheological Damper Using Hybrid Optimization Approach by Ali Fellah Jahromi, Rama B. Bhat, Wen-Fang Xie

“…The parameters of the model are identified using an experimental data based hybrid optimization approach which is a combination of Genetic Algorithm and Sequential Quadratic Programming approach. …”
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A New System Reliability Optimization Model Based on Swapping Existing Components by Yuxiong Li, Xianzhen Huang, Xinong En, Pengfei Ding

“…Replacing failed components with other functioning components properly in the original system can be an attractive way for improving system reliability. This paper proposes a new system reliability optimization model to achieve optimal component reliability and the ideal component-swapping strategy under a certain set of constraints. …”
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Differential Evolution for Optimizing Model Parameters in Simulation of Direct Dimethyl Carbonate Synthesis by Outi Ruusunen, Riitta Keiski, Mika Ruusunen

“…The Differential Evolution (DE) algorithm was applied to optimize parameters of the model. …”
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A New Algorithm Model Based on Extended Kalman Filter for Predicting Inter-Well Connectivity by Liwen Guo, Zhihong Kang, Shuaiwei Ding, Xuehao Yuan, Haitong Yang, Meng Zhang, Shuoliang Wang

“…Given that more and more oil reservoirs are reaching the high water cut stage during water flooding, the construction of an advanced algorithmic model for identifying inter-well connectivity is crucial to improve oil recovery and extend the oilfield service life cycle. …”
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A model for placing electric vehicle charging stations in megapolis based on the sparrow search algorithm by Sizhuo Du, D. V. Kapski

“…First, the main factors of placing electric vehicle charging stations are analyzed from different points of view, a multi-purpose model for choosing the address of the charging station is built, an algorithmic model is proposed to improve the sparrow search algorithm as the basis for a specific solution method, and finally, the effect of applying the model and solution method is verified by analyzing examples. …”
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Construction of Prioritized T-Way Test Suite Using Bi-Objective Dragonfly Algorithm by Mashuk Ahmed, Abdullah B. Nasser, Kamal Z. Zamli

“…In software testing, effective test case generation is essential as an alternative to exhaustive testing. For improving the software testing technology, the t-way testing technique combined with metaheuristic algorithm has been great to analyze a large number of combinations for getting optimal solutions. …”
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Research and application of intelligent learning path optimization based on LSTM-Transformer model by Jinling Wang, Wandong Chai

“…Experimental comparison shows that compared with the traditional learning path recommendation algorithm, the optimization strategy based on the LSTM-Transformer model has achieved remarkable results, with the learner's knowledge mastery rate greatly increased from 75 % to 95 %, the learning time shortened by about 25 %, and the learning satisfaction also increased from 70 % to 90 %, which verifies the research hypothesis and fully proves that the LSTM-Transformer model has high application value in intelligent learning path optimization.…”
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Design Optimization of Parameters for Resolver Software Decoding Based on Surrogate Model Management by DENG Yu, LING Yuelun, WU Zuolai, PENG Zaiwu, WANG Jun

“…Finally, a genetic algorithm (GA) was utilized to optimize parameters in the resolver software decoding system through a solving process, and a partial encryption method was introduced to iteratively update the surrogate model, yielding a partially optimal solution that meets the error requirements. …”
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Validation of a teaching model instrument for university education in Ecuador through an artificial intelligence algorithm by Jenniffer Sobeida Moreira-Choez, Tibisay Milene Lamus de Rodríguez, Aracelly Fernanda Núñez-Naranjo, Ángel Ramón Sabando-García, María Belén Reinoso-Ávalos, Cynthia Michel Olguín-Martínez, Daniel Omar Nieves-Lizárraga, Julieta Elizabeth Salazar-Echeagaray

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Co-Optimization of Vibration Suppression and Data Efficiency in Robotic Manipulator Dynamic Modeling by Xiaowei Han, Kunru Wu, Nanmu Hui

“…Finally, the PSO algorithm is applied to optimize the hyperparameters of the BLS network, achieving global model optimality. …”
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Slope stability prediction under seismic loading based on the EO-LightGBM algorithm by Ning Ma, Ning Ma, Yuqi Zhang, Zaizhen Yao

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Online Vulnerability Assessment in Cascading Failure Analysis Using an Intelligence Monitoring Model by Saber Armaghani, Zahra Moravej

“…Thus, in this paper, Demand Response modeling will be based on determining the cost of electric energy consumption in the emergency of the network in such a way as to cause a shift of consumption to improve the performance of the network. …”
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Hybrid optimization driven fake news detection using reinforced transformer models by Ganesh Karthik M, Khadri Syed Faizz Ahmad, Sai Geetha Pamidimukkala, Asha Prashant Sathe, Sirisha G.N.V.G, Sitha Ram M, Koteswararao Ch

“…The model is further optimized using PSODO, a hybrid Particle Swarm Optimization and Dandelion Optimization algorithm, addressing limitations such as slow convergence and local optima entrapment. …”
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ONBOARD FUEL PUMP FAULT DIAGNOSIS BASED ON IMPROVED SUPPORT VECTOR MACHINE AND EXPERIMENTAL RESEARCH by LIANG Wei, JING Bo, JIAO XiaoXuan, QIANG XiaoQing, LIU XiaoDong

“…Meanwhile,the fault feature vectors are used to train and validate this classification model. The experimental results show that this method not only can improve the classification accuracy on fault diagnosis,but also can optimize the use of sensors by using only one vibration sensor and one pressure sensor to recognize the fault signals.…”
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Optimizing Location of Car-Sharing Stations Based on Potential Travel Demand and Present Operation Characteristics: The Case of Chengdu by Yu Cheng, Xu Chen, Xiaohua Ding, Linting Zeng

“…This study aims to use different data source with statistical models and machine learning algorithm to help car-sharing operator to choose the optimal location of new stations and adjust the location of existing stations. …”
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HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction by Madhusmita Das, Biju R. Mohan, Ram Mohana Reddy Guddeti

“…In pursuit of enhancing the defect prediction accuracy of the SoMLDP model, this paper designed two novel hybrid swarm-optimization algorithms (SOAs) referred to as gravitational force grasshopper optimization algorithm-artificial bee colony (GFGOA-ABC), and levy flight grasshopper optimization algorithm-artificial bee colony (LFGOA-ABC) algorithms. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…Then, the FPN model is improved: based on the prior knowledge of bolts, the convolutional network is used to achieve bottom-up feature extraction, the bilinear interpolation method is used to transfer the high-level semantic information of the features to each level from top to bottom, the convolution filtering method is used to laterally strengthen the information fusion of high-level semantic features and high-resolution features, and a more optimized feature expression of bolts with missing pins is obtained. …”
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