Formation of a Strategy for Increasing the Efficiency of Operation of Distribution Electrical Grids at the Stage of Pre-Design Works by A. V. Zhurakhivskyi, Z. M. Bakhor, A. Ya. Yatseiko, V. H. Hapanovych

“…This allows formalizing the procedure for the choice and implementation the outlined measures as early as at the stage of pre-design formation of the modernization and reconstruction strategy so to provide an efficient use of funds for the reconstruction and technical retooling of distribution electrical grids in order to improve the quality of their operation. The mathematical model and the algorithm for the choice of the optimal technical measure for the reconstruction of the mainline taking into account the prospects for development that had been developed was tested during the development of the optimal strategy for the development of 6–10 kV distribution electrical grids in the Western region of Ukraine.…”
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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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Crashworthiness and optimization for foam-filled multi-layer composite lattice structures by Jiye Chen, Wangwang He, Hai Fang, Yong Zhuang, Zhixiong Zhang, Yufeng Zhao

“…For the FMCLS with double-layer dislocation cells or trapezoidal cells, the crush force efficiency (CFE) achieved average values of 44.86 % or 50.47 %, respectively, which were higher than those of the other types of FMCLSs. To obtain the optimal designs of the FMCLSs, metamodels and the MOPSO algorithm were utilized, with the specific energy absorption (SEA) and peak crushing force (PCF) selected as the two objectives. …”
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Optimization of Driving Axle Housing of Dump Truck based on Robustness Selection by Ronghui Lin, Peng Zhou

“…Three groups of 9 optimization sizes are obtained Through the deterministic optimization by multi-objective Genetic Algorithm. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…Subsequently, a hybrid optimization method is designed, combining the Genetic Algorithms with particle swarm optimization to improve the model’s global search capability and local convergence speed. …”
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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
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Research on Life Attenuation of Lithium-Ion Batteries Based on IC Curves and Voltage Hybrid Evaluation Algorithm by Xiaorong Huang, Wanwei Wang, Zhijun Guo, Xiliang Dai, Maoquan Ye, Danyu Tian

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Optimal design of solar cells grid electrodes based on quadratic curves by Yongjiang Liu, Kai Li, Bo Zhou, Xiangquan Li, Peizheng Li

“…This paper presents an optimization methodology employing width-varying quadratic curves to parameterize grid electrode profiles, coupled with a comprehensive power loss model. …”
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Optimizing concrete strength: How nanomaterials and AI redefine mix design by Dan Huang, Guangshuai Han, Ziyang Tang

“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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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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A Method for Solving LiDAR Waveform Decomposition Parameters Based on a Variable Projection Algorithm by Ke Wang, Guolin Liu, Qiuxiang Tao, Luyao Wang, Yang Chen

“…First, using a variable projection algorithm, we separated the linear (amplitude) and nonlinear (center position and width) parameters in the Gaussian function model; the linear parameters are expressed with nonlinear parameters by the function. …”
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Ant Colony Optimization Using Common Social Information and Self-Memory by Yoshiki Tamura, Tomoko Sakiyama, Ikuo Arizono

“…Ant colony optimization (ACO), which is one of the metaheuristics imitating real ant foraging behavior, is an effective method to find a solution for the traveling salesman problem (TSP). …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. …”
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Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning by Mohammad D. Alahmadi, Ahmed S. Alzahrani

“…The increasing presence of heavy connected vehicles (HCVs) in urban traffic necessitates optimized signal-control strategies to improve efficiency. …”
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Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network by Feng-Ping An

“…Therefore, this paper starts from the perspective of network optimization and improves the nonlinear modeling ability of the network through optimization methods. …”
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Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study by Shaik Hussain, Rajitha Morampudi, Priyamvada K., Bhargavi R. Naveena

“…This study compares Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), and Genetic Algorithm (GA) on three platforms : a local computer, a local computer with quantum integration, and an IBM quantum machine. …”
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Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…We propose a method that integrates advanced algorithms to identify and eliminate redundant movements, optimize the toolpaths, and improve the machining strategies. …”
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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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Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data. by Bo-Young Kim, Jung Hoon Park, Hye-Yeong Jo, Soo Kyung Koo, Mi-Hyun Park

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Hyperspectral Estimation of Chlorophyll Content in Ginseng Fruit Leaves Based on Wavelet Transform and VCPA-GA Algorithm by Guo Jinfeng, Zhang Zhicong, Umut Hasan, Zhou Zhongye, Xu Wenyu, Yusup Ahmat

“…This is because the wavelet transform process has some errors that increase with the number of decomposition layers. (2) The VCPA-GA hybrid variable selection algorithm merges the strengths of the VCPA and GA, addressing the tendency of the VCPA to select fewer variables and overcoming GA's limitations in handling many variables which can lead to overfitting, providing a theoretical basis for estimating ginseng fruit LCC using hyperspectral remote sensing. (3) Among the four machine-learning models, predictions from to 1-2 and 6-7 layers were generally lower than those of the 0 layer, while predictions from the 3–5 layers are higher, showing an overall trend of initial increase followed by a decrease as the number of wavelet decomposition layers increased. (4) Ginseng fruit leaf hyperspectral data processed by the DWT-VCPA-GA algorithm with a 4-layer DWT spectrum yielded the best predictive performance in the BP-AdaBoost regression model, with R2=0.919, mean absolute percentage error = 2.090%, and relative percentage difference = 3.900. (5) After optimizing the BPNN regression model with various algorithms, only some optimized models improved their predictive performance and accuracy to a certain extent, making the choice of the right optimization algorithm crucial for model improvement.…”
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