Artificial Intelligence and MCDA in Circular Economy: Governance Strategies and Optimization for Reverse Supply Chains of Solid Waste by Joel Joaquim de Santana Filho, Arminda do Paço, Pedro Dinis Gaspar

“…The results indicate that hybrid MCDA-AI models, employing techniques, such as TOPSIS, AHP, neural networks, and genetic algorithms, enhance decision-making automation, reduce costs, and improve waste traceability. …”
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A Hybrid Automata-Driven Machine Learning Framework for Real-Time Energy Optimization in Smart Buildings by Rikame Rajashri, Ranjan Mritunjay Kr., Jadhav Monali, Wankhede Shrushti, Bankar Sakshi, Bachhav Pranjal

“…Not only does the framework optimize the use of resources, but also it minimizes carbon footprint as well as costs of operation for a more efficient and sustainable smart city infrastructure.…”
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Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…Stress-testing under scenarios such as 48-hour grid failure, signal-based cyberattacks, and 40% PV output curtailment reveals substantial gains: operational costs are reduced by 9.3%, resilience scores improve by over 20% in adverse conditions, and convergence speed increases by 42% relative to classical optimization. …”
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Comparative techno-economic analysis of grid-connected solar PV-battery and PV-fuel cell systems for educational institutions sustainable academic laboratories by Takele Ferede Agajie, Fuseini Seidu Ibrahim, Isaac Amoussou, Elsabet Ferede Agajie, Eriisa Yiga Paddy, Yayehyirad Ayalew Awoke, Wirnkar Basil Nsanyuy, Mohit Bajaj

“…Techno-economic decision criteria were implemented using MATLAB. Three algorithms were used: Teaching–Learning-Based Optimization (TLBO), Water Cycle Algorithm (WCA), and Improved Grey Wolf Optimization (I-GWO). …”
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The effect of using the algorithm of restrictive intraoperative fluid therapy, early immune enteral nutrition, and early patient mobilization on orthotopic liver transplantation ou... by A. M. Dzyadz'ko, M. L. Katin, O. A. Chugunova, A. F. Minov, E. G. Oganova, E. O. Santotskiy, A. E. Shcherba, O. O. Rummo, I. I. Kanus

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Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…The results indicate that: ① The improved LSTM model demonstrates superior performance in simulating the Zuli River, validating the adaptability of the improved strategies for complex hydrological processes. ② The GWO algorithm significantly enhances the model's prediction accuracy in the basin, confirming the effectiveness of optimization algorithms in parameter calibration. ③The GWO-LSTM-Attention model requires further validation and optimization for future daily-scale simulations and monthly runoff reconstruction.…”
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Design and energy management research of integrated microgrid with light storage and charging with double-layer optimization scheduling model by Pan Zhai

“…On the basis of considering the uncertainty of photovoltaics, a dual layer optimization scheduling structure with reduced operating costs and equipped with supercapacitors has been proposed. …”
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Research on energy storage planning methods for distributed renewable energy integrated rural power distribution networks by Haoshuai Jia, Renqing Feng, Hai Jiang, Chao Gao, Yue Zhao, Rui Zhang, Ziyi Xuan

“…The optimal locations and capacities of energy storage systems are determined using YALMIP toolbox and the beetle swarm optimization (BSO) algorithm, and the proposed method is validated on a modified IEEE 33-bus system. …”
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Algorithm for assigning different 6-month short-term chemotherapy regimens in patients with drug-resistant tuberculosis: how to make the right choice for the clinician by Yu.I. Feshchenko, N.A. Lytvynenko, L.M. Protsyk, M.V. Pohrebna, Yu.O. Senko

“…For patients with pre-XDR-TB, the BPaL regimen offers the best balance of efficacy, tolerability, and cost-effectiveness. The proposed prescription algorithms enable a personalized treatment approach and improve therapeutic outcomes.…”
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Collaborative Optimization of Passenger Control Strategy and Train Operation Plan with Variable Formations for a Rail Transit Network by Yonghao Yin, Jun Chen, Wenrui Zhao

“…We proposed a passenger control strategy and train operation plan collaborative optimization (PCS&TOP) model to schedule the train operation that improves the efficiency of passengers’ travel and reduces the cost of train operation for a rail transit network. …”
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Artificial Intelligence-Driven Approach to Optimizing Boiler Power Generation Efficiency: The Advanced Boiler Combustion Control Model by Kyu-Jeong Lee, So-Won Choi, Eul-Bum Lee

“…Consequently, achieving stable combustion control of these gases is critical for improving boiler efficiency. This study developed the advanced boiler combustion control model (ABCCM) by combining the random forest (RF) and classification and regression tree (CART) algorithms to optimize the combustion of steam power boilers using steel by-product gases. …”
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Tackling the Optimal Phasor Measurement Unit Placement and Attack Detection Problems in Smart Grids by Incorporating Machine Learning by Ramzi Al-Sharawi, Abdelfatah Ali, Mostafa Shaaban, Nasser Qaddoumi, Mohamed S. Abdalzaher

“…Existing research primarily addresses cybersecurity by focusing on the optimal placement of phasor measurement units (PMUs) to ensure topological observability and minimize system costs, followed by developing AI-based attack detection algorithms. …”
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Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction by Bokun Ning, Fang Zhao, Haiyong Luo, Dan Luo, Wenhua Shao

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Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. …”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. …”
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Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics by Peiqi Li, Zhiwei Ai, Mufan Zhang

“…The optimization utilized the NSGA-II algorithm. Additionally, a virtual prototype with rigid-flexible coupling was created for simulation assessments pre- and post-optimization. …”
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Synergistic Effects of Energy Storage Systems and Demand-Side Management in Optimizing Zero-Carbon Smart Grid Systems by Zeyad A. Almutairi, Ali M. Eltamaly

“…An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. …”
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Path planning of unmanned ships based on A* and dynamic window approach by FU Long, SHEN Zhen, TAO Hao, HAN Yunjun, DONG Xisong, XIONG Gang

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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

“…This paper uses a particle swarm optimisation (PSO) algorithm to determine the optimal values for the injected components. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…By using Stochastic Forest, an improvement in decision accuracy can be attained to the extent of 15–20%, together with a cut in costs of about 10%. …”
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