Multi-objective optimization of integrated energy system considering customer satisfaction by YU Wuyue, JIA Yuchen, HUO Limin, WEN Peng, GAO Liai

“…A multi-objective optimization function with improved customer satisfaction, economy and carbon emission is constructed, and MAPSO (multi-group adaptive particle swarm optimization) algorithm is used for optimization analysis, and the Pareto optimal frontier solution sets in different scenarios are obtained. …”
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Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

“…The estimated subsurface parameters closely match with well data and prior studies, emphasizing the algorithm’s practical effectiveness. This integrated approach significantly advances the interpretation of magnetic datasets by improving both the accuracy and resolution of subsurface parameters estimation within the framework of idealized geometric models.…”
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Automatic detection and classification of drill bit damage using deep learning and computer vision algorithms by Xiongwen Yang, Xiao Feng, Chris Cheng, Jiaqing Yu, Qing Zhang, Zilong Gao, Yang Liu, Bo Chen

“…The experimental results demonstrate that the proposed method significantly enhances the accuracy of bit damage detection and classification while also providing substantial improvements in processing speed and computational efficiency, offering a valuable tool for optimizing drilling operations and reducing costs.…”
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Dynamic Analysis and Efficient Numerical Algorithm for Rocking Response of Freestanding Packages Under Transportation Excitations by Zhenmin Qi, Dapeng Zhu

“…Experimental validation under sinusoidal and numerical analysis with random excitations confirms the algorithm’s effectiveness in predicting rocking behavior. …”
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM by Ahmed Mohammed Ahmed Alsarori, Mohd Herwan Sulaiman

“…Cardiovascular diseases (CVD) remain the leading cause of mortality worldwide, emphasizing the urgent need for accurate and efficient predictive models. This study proposes a dual-output deep learning model based on a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, optimized using the Evolutionary Mating Algorithm (EMA). …”
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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification by Hang Yanping, Zheng Haixia, Yang Minmin, Wang Nan, Kong Miaomiao, Zhao Mingming

“…The algorithm enhances cancer detection while ensuring data privacy. …”
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Water Supply Scheduling for Cross-basin Reservoir Groups Based on Improved Scheduling Diagram by ZHAO Siqi, XU Wei, CHEN Si, WANG Sufan, YANG Yi

“…To exploit the scheduling potential of cross-basin reservoir groups by employing runoff information,this paper proposes an improved reservoir scheduling diagram to retain simplicity and intuitiveness.Taking the Xiajiankou,Fengyan,and Nanpeng reservoirs in Banan District of Chongqing as an example,it adopts the POA algorithm to build a joint scheduling model of water diversion and water supply for the cross-basin reservoir groups by a simulation-optimization approach.Meanwhile,three scenarios of the current situation scheduling,optimized scheduling with conventional scheduling diagrams,and optimized scheduling with improved scheduling diagrams are set up to evaluate the water diversion and supply performance of reservoirs and analyze the influence of uncertainty runoff information on the scheduling performance.The results are as follows:① The improved scheduling diagram performs best in the long series scheduling,and it can increase the annual average water supply of the reservoir group by 6.87% and reduce the abandoned water by 87.58% compared with the current situation scheduling;② In a dry year,the method can reduce 486.3×10⁴ m³ of water shortage and increase 477.6×10⁴ m³ of water for power generation based on the current situation scheduling;③ When considering the runoff information uncertainty,the water supply of the improved scheduling diagram is 3.37% lower than the ideal case but is still 5.96% more than the conventional optimization.The results are conducive to making scientific decisions and improving the water supply effect.…”
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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…Finally, the actual blasting effect of tunnel construction is tested and the optimization algorithm model of tunnel fault drilling and blasting parameters is established. …”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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Optimal control strategy for trains in emergency self-propelled running conditions by ZHU Yutong

“…In conclusion, the designed coasting algorithm based on the optimal constant speed can effectively reduce the total energy consumption of emergency self-propelled train operation, thereby improving the self-rescue success rate of high-speed trains.…”
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Bi-Objective Optimization of Product Selection and Ranking Considering Sequential Search by Yuyang Tan, Hao Gong, Chunxiang Guo

“…To address this gap, we study a bi-objective product selection and ranking (BP-SS) problem considering sequential search, aiming to jointly optimize the expected revenue and market share. We first develop a two-stage choice model with consideration sets to capture how sequential search influences customer decision-making. …”
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Solution Approach to the Minimum Spanning Tree Problem in Tsukamoto Fuzzy and Fermantean Fuzzy Environments by Desli de Haas, Citra Palembang, Aziz Rumakefing

“…With the help of Numerical examples, the solution technique for the proposed FFMST model is explained. It aims to modify the Prims algorithm for oriktade graphing and the optimal result processing algorithm for re-graphing in Fuzzy Fermatean ( FFN )-miljö. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

“…We generated a stratified 60‐20‐20 train‐validate‐test split to assess model generalizability. We trained four machine learning algorithms including logistic regression, Random Forest, AdaBoost and XGBoost. …”
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Collaborative Optimization Strategy for Dependent Task Offloading in Vehicular Edge Computing by Xiting Peng, Yandi Zhang, Xiaoyu Zhang, Chaofeng Zhang, Wei Yang

“…The task-offloading problem is modeled as a Markov Decision Process, and an improved twin-delayed deep deterministic policy gradient algorithm, LT-TD3, is introduced to enhance the decision-making process. …”
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Tool wear monitoring method based on AMIDBOAB and imbalanced data optimization by Guan-Hua Xu, Hong-Yu Wu, Bo Tang, Jun-Long Xu

“…Introducing circle chaotic mapping, Levy flight strategy, and adaptive variable inertia weight, a multiple improvement dung beetle optimizer algorithm is proposed to optimize the parameters of the base classifier in the adaptive boosting model. …”
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Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

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Improving the Integrity of a Voting Process with Biometric Authentication and Data Encryption by Walter M. Molina, Lino R. Mac Kay, Daniel Subauste

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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several DL algorithms focusing only on training and testing the models on the planning MRI only. …”
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Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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RESEARCH ON THE OPTIMAL DESIGN METHOD OF U-SHAPED SECTION CONTAINMENT RING

“…U-shaped containment ring is usually used as protection device for turbine starters.Under the condition that the turbine rotor is contained,structural optimization of the U-shaped section containment ring was carried out to obtain a light and inclusive structure,which improved aircraft safety and thrust-to-weight ratio.An optimal design method for U-shaped cross section containment ring was proposed.The method adopted the optimal Latin hypercube design,numerical simulation,response surface modeling,and multi-island genetic algorithm to achieve the optimal design of multiple parameters of containment rings cross section.By combining simulation and experiment,the influence weights of different structural parameters on the residual kinetic energy of debris and the volume of containment rings were analyzed.The influence of different structural parameters of Ushaped containment ring on the containment results was studied.Containment test was carried out to verify the optimized containment ring.The results show that the thickness of the containment ring has the greatest influence on the residual kinetic energy of the debris,and the weight ratio is 38%.The main structural parameters affect the inclusion effect are thickness and groove depth.The error of inclusion ring deformation is less than 2%in the comparison between simulation and test results,which indicates that the optimization design method proposed is reasonable and reliable.The research results can provide prior knowledge and optimization methods for the quality reduction of U-shaped containment ring structures.…”
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