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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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Key AI techniques, including support vector machines (SVMs) (7.90% of studies), decision trees, and gradient-boosting models, offer substantial improvements in cost prediction and resource optimization. …”
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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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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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Study on Optimal Decision of Unit Commitment with Flexible Reserve Participation in Power Grid by ZHOU Yi, LI Yichen, FU Youshu, QIN Kangping, ZHU Wen, FAN Dongqi

“…Secondly, a unit combination model considering the flexible reserve is established with the objective function of minimizing the total operating cost of the system, and the optimization algorithm program is written in the Lingo environment to optimize a variety of reserve resources. …”
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INNOVATIVE MECHANISMS FOR IMPLEMENTING STATE ECONOMIC POLICY FOR POST-WAR RECONSTRUCTION OF UKRAINE: QUANTUM TRANSFORMATIONS AS A DRIVER OF DEVELOPMENT by Oleksiy Shkuratov, Liudmila Antonova, Roman Dzyuba

“…It has been proven that it is possible to improve the situation only if a balanced state investment policy for quantum transformation of the country is developed and implemented. …”
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Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…Notably, as the number of channels increases, S-SE stabilizes while fairness continues to improve, approaching optimal levels in diverse system configurations. …”
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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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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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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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Optimizing Robotic Arm Learning: Curiosity-Driven Deep Deterministic Policy Gradient by Liu Jiarun

“…However, collecting the large- scale real-world data is costly and impractical, making simulation environments essential for optimization. …”
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Towards a digital twin: Digitization and model-based optimization of the innovative high-gradient magnetic separatorMendeley Data by Marko Tesanovic, Torben Bardel, Robin Karl, Sonja Berensmeier

“…Optimization results indicated a theoretical 4% productivity gain and a 3 percentage point yield improvement, while exposing critical design constraints in the HGMS chamber.These findings underscore the potential of digital twins to accelerate process optimization and reduce development costs through in-silico experimentation. …”
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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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Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
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Expansion of Output Spatial Extent in the Wavenumber Domain Algorithms for Near-Field 3-D MIMO Radar Imaging by Yifan Gong, Limin Zhai, Yan Jia, Yongqing Liu, Xiangkun Zhang

“…Simulation results show that the improved wavenumber domain algorithms effectively suppress the aliasing energy of each sub-block while maintaining the advantage of low time complexity. …”
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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

“…The proposed GNN-RL-APF-Lagrangian algorithm achieves a 96.43% success rate in sparse obstacle environments and 89.77% in dense obstacle scenarios, representing improvements of 59% and 60%, respectively, over baseline GNN-RL approaches. …”
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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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Advancing GNOS-R Soil Moisture Estimation: A Multi-Angle Retrieval Algorithm for FY-3E by Xuerui Wu, Junming Xia, Weihua Bai, Yueqiang Sun

“…By leveraging multi-angle data, the algorithm achieves significantly improved retrieval accuracy, with root mean square errors of 0.0235, 0.0264, and 0.0191 (g/cm³) for bare, low-vegetation, and dense-vegetation areas, respectively. …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. …”
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Individualized post‐operative prediction of cochlear implantation outcomes in children with prelingual deafness using functional near‐infrared spectroscopy by Zhe Chen, Xue Zhao, Haotian Liu, Yuyang Wang, Zhikai Zhang, Yuxuan Zhang, Yuhe Liu

“…Both classification and individualized regression models were constructed to predict post‐CI behavioral improvement from fNIRS data using support vector machine (SVM) learning algorithms. …”
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