Carbon Emission Prediction of Freeway Construction Phase Based on Back Propagation Neural Network Optimization by Lin Wang, Jiyuan Zhu, Haoran Zhu, Wencong Xu, Zihao Zhao, Xingli Jia

“…Furthermore, we integrated multiple strategies to improve the northern goshawk optimization algorithm and optimize the BP neural network, thereby establishing a carbon emission prediction model for the highway construction phase. …”
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Optimal Skip-Stop Schedule under Mixed Traffic Conditions for Minimizing Travel Time of Passengers by Sun Feng, Zhu Wen-tao, Ye Ying, Wang Dian-hai

“…This paper proposes an optimization model for designing skip-stop service that can minimize the total travel time for passengers. …”
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Coordinated Optimization and Operational Strategy for Multi-type Energy Storage in Regional Integrated Energy Systems by Mingfei GAO, Zhonghe HAN, Bin ZHAO, Peng LI, Di WU

“…And then, by taking into account three objectives of economy, environment, and energy efficiency, the model was used to optimize the operational parameters of systems by utilizing the improved multi-objective particle swarm optimization (MOPSO) algorithm in conjunction with the TOPSIS method. …”
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Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment by Jing Zhang, Jingjing Liu, Zhong Wan

“…For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. …”
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Intelligent generation and optimization of resources in music teaching reform based on artificial intelligence and deep learning by Ding Cheng, Xiaoyu Qu

“…Therefore, the constructed model can not only generate high-quality personalized melody, but also shows a significant improvement in improving user experience and learning effect, providing reference direction for the generation and optimization of intelligent resources in music teaching.…”
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Fast and Accurate Direct Position Estimation Using Low-Complexity Correlation and Swarm Intelligence Optimization by Yuze Duan, Zuping Tang, Jiaolong Wei, Jie Sun, Kaixian Ying

“…Both extensive simulations and real GNSS data experiments further validate that the proposed framework, incorporating the ADBO algorithm, achieves improved positioning accuracy compared to traditional positioning methods while outperforming traditional search algorithms and other swarm intelligence algorithms in both accuracy and computational efficiency.…”
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Shipboard power system dynamic reconfiguration optimization strategy considering time-varying load characteristics by Qihuan WU, Zhiyu ZHU, Weihan HAO, Denghao YANG, Cheng XU

“…Next, an improved inertial particle swarm optimization algorithm is used to solve the optimization model. …”
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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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Numerical Simulation and Optimization of Wind Effects of Porous Parapets on Low-Rise Buildings with Flat Roofs by Ye Qiu, Bingbing San, Youyi Zhao

“…This paper presents a procedure to optimize the porosity of parapets to improve the aerodynamic behavior of low-rise buildings with flat roofs, by coupling an optimization algorithm and computational fluid dynamics (CFD) simulations. …”
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DBO-DELM Method for Predicting Rolling Forces in Cold Rolling by LI Xiaoyang, PIAO Chunhui, WANG Xuelei, ZHANG Mingzhi

“…Aiming at the problems of many assumptions, large computational errors and poor generalisation performance of the traditional rolling force prediction model, a cold rolling force prediction model (DBO-DELM) using the dung beetle optimizer algorithm (DBO) to optimise the deep extreme learning machine (DELM) is proposed. …”
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Energy Interaction and Energy Storage Sharing Optimization Method for Users, Base Stations, and Charging Stations by HU Long, FANG Baling, FAN Feilong, CHEN Dawei, LI Xinxi, ZENG Run

“…Next, incorporating 0-1 integer variables, a solution method utilizes the adaptive differential evolution algorithm combined with the mixed-integer optimization theory. …”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

“…Ten topographic and environmental conditioning factors were selected as model inputs. We first employed the Tree-based Pipeline Optimization Tool (TPOT), an evolutionary AutoML algorithm, to construct baseline ensemble models using Gradient Boosting (GB), Random Forest (RF), and XGBoost (XGB). …”
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A cluster-optimized regulation method for distribution networks considering distributed photovoltaic heterogeneous characteristics by Junhao Li, Xin Wang, Qi Guo, Chunzhi Yang, Yizhe Chen, Ruifeng Zhao, Ming Li

“…Further, a DN cluster-optimized model considering the DPV heterogeneous characteristics is constructed to achieve multi-objective optimization of the integrated DN operation cost and node voltage deviation. …”
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Co-Optimization of Market and Grid Stability in High-Penetration Renewable Distribution Systems with Multi-Agent by Dongli Jia, Zhaoying Ren, Keyan Liu

“…The methodological innovations primarily include an enhanced scheduling algorithm for coordinated optimization of renewable energy and energy storage, and a dynamic coordinated optimization method for EV clusters. …”
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Optimal Scheduling of Biomass-Hybrid Microgrids with Energy Storage: An LSTM-PMOEVO Framework for Uncertain Environments by Zichong Wang, Yingying Zheng

“…Finally, a public dataset was utilized for the experiments to verify the performance of the proposed algorithm. Comparisons and discussions show that the proposed optimization strategies significantly improve the performance of PMOEVO, demonstrating marked advantages over six classical algorithms. …”
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Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data by Zhihong Li, Han Xu, Shiyao Qiu, Jun Liu, Kairan Yang, Jiahao Wu

“…To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. …”
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Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters by Wenmin Wang, Cuijie Diao, Wenqing He, Zhihong Jin, Zaili Yang

“…Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. …”
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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. …”
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Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…The MTSP ( multiple traveling salesman problem) is introduced to construct an optimized train stock utilization model during the transition period from peak to off-peak passenger flow in urban rail transit. …”
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