Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis by Dominik Takács, Ambrus Zelei

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Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…Solving the problem of multi-criteria optimization of the drone team flight route planning made it possible to reduce the cost of monitoring critical infrastructure facilities while improving its efficiency and accuracy. …”
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MATHEMATICAL MODEL OF DENGUE HEMORRHAGIC FEVER SPREAD WITH DIFFERENT LEVELS OF TRANSMISSION RISK by Faishal Farrel Herdicho, Nabil Azizul Hakim, Fatmawati Fatmawati, Cicik Alfiniyah, John Olajide Akanni

“…Key model parameters were estimated using DHF case data from East Java in 2018, employing a genetic algorithm (GA) to optimize the estimation process. …”
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Multi-Objective Optimization Research Based on NSGA-II and Experimental Study of Triplex-Tube Phase Change Thermal Energy Storage System by Yi Zhang, Haoran Yu, Yingzhen Hou, Neng Zhu

“…A multi-objective optimization method based on the elitist non-dominated sorting genetic algorithm (NSGA-II) was utilized to optimize the geometric dimensions (inner tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>1</mn></msub></semantics></math></inline-formula>, casing tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>2</mn></msub></semantics></math></inline-formula>, and outer tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>3</mn></msub></semantics></math></inline-formula>), focusing on heat transfer efficiency (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ε</mi></semantics></math></inline-formula>), heat storage rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mi>t</mi></msub></semantics></math></inline-formula>), and mass (<i>M</i>). …”
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Evaluation of Environmental Factors Influencing Photovoltaic System Efficiency Under Real-World Conditions by Krzysztof Pytel, Wiktor Hudy, Roman Filipek, Malgorzata Piaskowska-Silarska, Jana Depešová, Robert Sito, Ewa Janiszewska, Izabela Sieradzka, Krzysztof Sulkowski

“…In order to advance the analysis beyond conventional methods, a linear regression model was developed in which the model weights were optimized using evolutionary algorithms, allowing for a more robust assessment of the contribution of each parameter. …”
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Enhancing Adaptive Spectrum Access: An Intelligent Reflecting Surface Assisted CRN for Future Wireless Communication by Vishwas Srivastava, Binod Prasad

“…To address this, we propose an intelligent reflecting surface (IRS)-assisted enhanced ASAM (EASAM) CR network (CRN). Additionally, we optimize the IRS phase shifts and ST&#x2019;s transmit power using the Grey Wolf Optimization (GWO) algorithm. …”
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Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery by Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen

“…Accurately identifying the distribution of vineyard cultivation is of great significance for the development of the grape industry and the optimization of planting structures. Traditional remote sensing techniques for vineyard identification primarily depend on machine learning algorithms based on spectral features. …”
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Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments by Amin Wen, Tonghua Wu, Xiaofan Zhu, Jie Chen, Jianzong Shi, Peiqing Lou, Dong Wang, Xin Ma, Xiaodong Wu

“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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Investigation on Circadian Regulation of Four-Primary LED Display Differed in People by GA by Wenhui Li, Junying Li, Yating Feng, Yi Lin, Haoyang Liu, Ruoping Lian, Qinzhen Lin, Jingyi Cui, Zixin Huang, Yaling Chai, Ziquan Guo, Lili Zheng, Zhong Chen

“…The main figures of merit of LED display performance are color gamut of Rec. 2020, luminous efficacy of radiation, correlated color temperature (CCT), and also non-visual parameters, such as circadian stimulus and melanopic efficacy of luminous radiation provided by Commission Internationale de l&#x0027;Eclairage (CIE) standard. Then, the genetic algorithm is adopted for performing the spectral optimization of four-primary LED display while many constraint conditions are set, such as CCT values (2700 K and 6500 K), CCT tolerance, and color distance (<italic>D</italic>_uv &lt; 0.01) in the CIE 1960 UCS color space. …”
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Cooperative Low-Carbon Trajectory Planning of Multi-Arrival Aircraft for Continuous Descent Operation by Cun Feng, Chao Wang, Hanlu Chen, Chenyang Xu, Jinpeng Wang

“…Firstly, this study analyzes the CDO phases of aircraft in the terminal area, establishes a multi-phase optimal control model for the vertical profile, and introduces a novel vertical profile optimization method for CDO based on a genetic algorithm. …”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Conclusions This study contributes to the refinement of CES-D by developing a machine learning-derived stratified screening version, offering an efficient and reliable approach that optimizes assessment burden while maintaining excellent psychometric properties. …”
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Optimizing Security of Radio Frequency Identification Systems in Assistive Devices: A Novel Unidirectional Systolic Design for Dickson-Based Field Multiplier by Atef Ibrahim, Fayez Gebali

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Artificial neural networks-based multi-objective optimization of immersion cooling battery thermal management system using Hammersley sampling method by Muhammed Donmez, Mehmet Ihsan Karamangil

“…Using the Hammersley method, various module designs are generated. Multi-objective optimization, using ANN-based multi objective genetic algorithms, is conducted on a 16S1P configuration at 4C discharge and 0.008 kg/s. …”
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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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Hyperspectral imaging for precision nitrogen management: A comparative exploration of two methodological approaches to estimate optimal nitrogen rate in processing tomato by Vito Aurelio Cerasola, Francesco Orsini, Giuseppina Pennisi, Gaia Moretti, Stefano Bona, Francesco Mirone, Jochem Verrelst, Katja Berger, Giorgio Gianquinto

“…PLSR outperformed the other algorithms in estimating N uptake (Relative Root Mean Square Error, RRMSE=21.8 %), while SVR better estimated NNI (RRMSE=10.2 %) and direct biomass (RRMSE=19.4 %). …”
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Heuristics Algorithms for a Heterogeneous Fleets VRP with Excessive Demand for the Vehicle at the Pickup Points, and the Longest Traveling Time Constraint: A Case Study in Prasitsu... by Sasitorn Kaewman, Raknoi Akararungruangkul

“…We developed two metaheuristics&mdash;a differential evolution (DE) algorithm and an adaptive large neighborhood search (ALNS)&mdash;to solve the problem. …”
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A Comparative Study Between Soft Actor-Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) Algorithms for Solar PV MPPT Control Under Partial Shading Conditions by Sampson E. Nwachukwu, Komla A. Folly, Kehinde O. Awodele

“…However, due to the intermittent nature of PV arrays, the Maximum Power Point Tracking (MPPT) algorithm is typically employed to optimize the system&#x2019;s energy production. …”
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A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort stud... by Xingjian Xiao, Xiaohan Yi, Zumin Shi, Zongyuan Ge, Hualing Song, Hailei Zhao, Tiantian Liang, Xinming Yang, Suxian Liu, Bo Sun, Xianglong Xu

“…Objective Our study aims to employ machine learning algorithms to predict the occurrence of gastric ulcers and develop an online tool to assess the risk of gastric ulcers for elderly individuals, both currently and in the future, while identifying important predictors. …”
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Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches by İnayet Burcu Toprak

“…In addition, Machine Learning algorithms were applied to predict hardness values. …”
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Quantitative structure-activity relationship study of some angiotensin-converting enzyme inhibitor drugs in the treatment of hypertension based on Monte Carlo optimization method by Shahram Lotfi, Shahin Ahmadi, Ali Azimi

“…The whole data set is randomly divided into three splits, and an individual model was created for each division. …”
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