Thermal performance and passive energy saving optimization of prefabricated houses in Xinjiang region by Juan Zhao, Rui Liu, Botao Zhou, Yunchao Fu, Yongcai Li, Wenjie Zhang

“…Compared to original scheme1, it effectively achieves a reduction in the annual cost value to 6037.09CNY, representing a decrease of 489.853CNY, along with an energy consumption of 9428.36 kWh, reflectiong a reduction by 13.48 %.This study provides experimental data and passive energy-saving optimization solutions for improving thermal performance in retrofitting prefabricated houses.…”
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Cancer Diagnosis Optimization With a Combination of Flexible THz Antennas and Machine Learning by M. Senthil Pandian, S. Deepa Nivethika, J. Idhikash, Vamsee N. Yashwanth, Aishwarya Shaji, Prabhakaran Paulraj

“…Whereas, the same antenna was designed and simulated with a model replicating human tissue with tumor, radiating at 0.88 THz with a return loss of −38 dB and gain of 9.6 dB. The optimization of the decision was done using the combination of K‐means and logistic regression algorithm to determine 95.06% efficiency.…”
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UAV-Based Pseudolite Navigation System Architecture Design and the Flight Path Optimization by Ruocheng Guo, Hong Yuan, Yang Zhang, Xiao Chen, Guanbing Zhang

“…The research results show that the flight path strongly guarantees navigation service performance with constraints on the operating cost. The ARMNSGA-III proposed in this paper can provide a 44.01% algorithm timeliness improvement compared to the NSGA-III in the flight path optimization, supporting rapid establishment and continuous service of the UAV-PNS in emergency scenarios.…”
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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…The optimization of biofuel production involves balancing multiple conflicting objectives such as yield maximization, cost minimization, and environmental impact reduction. …”
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A Comparative Study of EAG and PBIL on Large-Scale Global Optimization Problems by Imtiaz Hussain Khan

“…Evolutionary Algorithm with Guided Mutation (EAG) combines global statistical information and location information to sample offspring, aiming that this hybridization improves the search and optimization process. …”
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Adaptive optimization of electromyographic channels for intelligent prosthetic hands based on individual differences by Jianzhuang Zhao, Ye Tian, Yuxuan Wang, Weiye Ji, Mingchi Zhu

“…Intelligent prosthetic hands typically require an increase in the number of acquisition channels to improve gesture recognition accuracy, resulting in increased device complexity and cost. …”
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Multi-objective operation optimization method of microgrid considering the influence of electric vehicle by Tiefeng Xu, Xiaofang Meng, Fangfang Zheng, Yiduo Zhang, Xin Wu, Mingyang Li

“…Taking the minimum total operating cost and the minimum peak-valley difference of the microgrid in one day as the optimization objective, and considering many constraints such as power balance constraints and output constraints of distributed generation units, the multi-objective optimization function is transformed into a single-objective optimization function by linear weighting method, and the model is solved by particle swarm optimization algorithm. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. …”
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Structural design and optimization of egg carrier for dynamic egg slit detection platforms. by Ronghua Meng, Yuxiang Tian, Siwei Huang

“…Finally, motion simulation is carried out for the improved egg carrier, which verifies the optimized structure reasonableness.…”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…Compared to other commonly algorithms, this algorithm can simultaneously achieve higher detection accuracy and lower time cost for high volume intersections, offering good application prospects in vehicle road collaboration scenarios. …”
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Optimization of Resonant Arrays for Dynamic Wireless Power Transfer Using Adaptive Termination by Joao Dinis, Jose Alberto, Antonio J. Marques Cardoso

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Two-Stage Integrated Optimization Design of Reversible Traction Power Supply System by Xiaodong Zhang, Wei Liu, Qian Xu, Zhuoxin Yang, Dingxin Xia, Haonan Liu

“…The parallel cheetah algorithm is employed to solve this complex optimization problem. …”
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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. …”
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Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization by Yifei Bi, Jianing Luo, Jiwei Zhu, Junxiu Liu, Wei Li

“…Additionally, it introduces safety constraints through an artificial potential field (APF) to optimize these trajectories. Additionally, a constrained nonlinear optimization method further refines the APF-adjusted paths, resulting in the development of the GNN-RL-APF-Lagrangian algorithm. …”
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Multi-objective production scheduling optimization strategy based on fuzzy mathematics theory. by Heshuai Shen

“…Multi-objective production scheduling faces the problems of inter-objective conflicts, many uncertainty factors and the difficulty of traditional optimization algorithms to deal with complexity and ambiguity, and there is an urgent need to introduce the theory of fuzzy mathematics in order to improve the scheduling efficiency and optimization effect. …”
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Improving Efficiency of Rolling Mill Stand Electric Drives Through Load Alignment by Stanislav S. Voronin, Andrey A. Radionov, Alexander S. Karandaev, Roman A. Lisovsky, Boris M. Loginov, Mark A. Zinchenko, Vadim R. Khramshin, Ivan N. Erdakov

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Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge by Botian HAO, Yunfei DIAO, Ya WEI, Donghai XU

“…This approach increases biocrude yields, improves product quality, and reduces the cost of biomass HTL technology, thus facilitating industrial-scale application. …”
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How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…This study uses Artificial Neural Networks (ANNs) and multiple linear regression (MLR) models to explore the relationship between gait dynamics and the metabolic cost. Six nonlinear metrics—Lyapunov Exponents based on Rosenstein’s algorithm (LyER), Detrended Fluctuation Analysis (DFA), the Approximate Entropy (ApEn), the correlation dimension (CD), the Sample Entropy (SpEn), and Lyapunov Exponents based on Wolf’s algorithm (LyEW)—were utilized to predict the metabolic cost during walking. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…XGBoost achieved optimal performance with highest $$\text {AUC}$$ (0.956, 95% $$\text {CI}$$ : 0.952–0.961) and competitive clinical cost (5,496), representing 2.8% improvement over Random Forest. …”
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APG mergence and topological potential optimization based heuristic user association strategy by Zhirui HU, Meihua BI, Fangmin XU, Meilin HE, Changliang ZHENG

“…Methods:The network scalable degree was designed as a measure of scalability,and then a user association strategy to improve network scalable degree was studied by using optimization theory. 1) For modelling the optimization problem, firstly, the network coupling degree, representing the degree of association among nodes, was constructed to establish the mathematical relationship between the network scalable degree and AP group (APG).Thus,the problem of improving the network scalable degree was modeled as the problem of minimizing the network coupling degree.Then,a multi-objective optimization problem of minimum network coupling degree and maximum user rate was established to find the balance between network scalable degree and network service quality. 2) For solving the optimization problem,to avoid the high computational complexity,a heuristic user association strategy based on APG mergence and topological potential optimization was proposed.With the proposed algorithm,the number of APG could be reduced by APG mergence,and the number of APG that AP belongs to could be reduced by AP exiting APG. …”
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