Carbon emission prediction method for expressway construction period based on PSO-BP neural network by Quansheng ZHAO, Fei LI, Feng′ai GUO, Jianyou YU, Shizhao XU, Yunpeng HU, Xiaomeng CHU

“…To solve the problem of inaccurate carbon emissions prediction during the highway construction period, a method of optimizing the back propagation(BP) neural network by particle swarm optimization (PSO) algorithm was proposed to predict carbon emissions. …”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

“…In conjunction with the neural network algorithm, a bi-objective optimization model is further developed and solved to adjust scale factor of the Skyhook controller according to different running conditions. …”
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Battery Sizing Method for Microgrids—A Colombian Application Case by Andres Felipe Zamora-Muñoz, Martha Lucia Orozco-Gutierrez, Dany Mauricio Lopez-Santiago, Jhoan Alejandro Montenegro-Oviedo, Carlos Andres Ramos-Paja

“…Mixed integer linear programming (MILP) is used as optimization algorithm to size BESS, which is applied to an isolated community in Colombia located at Isla Múcura. …”
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Modeling 5G-NR User Blocking Probability in Conditional Handover-Enabled Heterogeneous Networks by Amiraslan Haghrah, Javad Musevi Niya, Jafar Pourrostam

“…To demonstrate the practical applicability of the proposed model, we present a case study involving a multi-objective optimization problem solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). …”
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Rotation reshapes sustainable potato production in dryland by reducing environmental footprints synergistically enhancing soil health by Hanyou Xie, Weiyan Wang, Ping He, Wencheng Ding, Xinpeng Xu, Xuelian Tan, Xiaowei Liu

“…Furthermore, the non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize regional cropping structure. …”
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Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data by Subhieh El-Salhi, Bashar Igried, Sari Awwad

“…Feature selection was performed using Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing, while ten machine learning models were implemented — ranging from Linear Regression and Decision Trees to Gradient Boosting, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) networks. …”
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A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

“…Using a Long Short-Term Memory (LSTM) algorithm optimized by Super SAPSO (Simulated Annealing Particle Swarm Optimization), the model forecasts server failures with improved accuracy, reducing False Alarm Rates and improving Failure Detection Rates. …”
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A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…The inertia weight $$\omega$$ and learning factor c were optimized to enhance the optimization ability of the particle swarm. …”
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DYMOS: A New Software for the Dynamic Identification of Structures by Fabrizio Gara, Simone Quarchioni, Vanni Nicoletti

“…DYMOS includes various state-of-art algorithms and tools for vibration-based modal identification and for optimal sensor placement (OSP), allowing for customization of analysis parameters and procedures with the aim of reducing the gap between the needs of professional practice and research. …”
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Multiple fixed-wing UAVs collaborative coverage 3D path planning method for complex areas by Mengyang Wang, Dong Zhang, Chaoyue Li, Zhaohua Zhang

“…This algorithm meticulously optimizes the operation, entry, and transition paths for each UAV, while also establishing evaluation metrics to refine coverage sequences for each area. …”
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Crash severity prediction using a virtual geometry-group-based deep learning approach with images-based feature representation by Nanon Sonnatthanon, Kasem Choocharukul

“…To address class imbalance, a combination of the Synthetic Minority over Sampling technique, Edited Nearest Neighbor, and Tomek Link algorithms are applied. A Virtual Geometry Group deep learning model, optimized using Bayesian optimization, is trained to maximize the F1-score and Area Under the Curve, ensuring high prediction performance. …”
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Spatial pattern and heterogeneity of green view index in mountainous cities: a case study of Yuzhong district, Chongqing, China by Aiping Gou, Xuyuan Wang, Jiangbo Wang, Chenjie Wang, Guanzheng Tan

“…This study investigates the spatial heterogeneity of the GVI and its influencing factors in Yuzhong District, Chongqing, a mountainous city in China. Deep learning algorithms were employed to calculate the green visibility of street view images, and Geographic Weighted Regression (GWR) and the Optimal Parameter-Based Geodetector (OPGD) were utilized to analyze the relationships between GVI and factors such as road physical attributes, the Normalized Difference Vegetation Index (NDVI), and topographic features. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. …”
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Real‐Time Parameter Identification and State of Charge Estimation of Electric Vehicle Batteries by A. Maheshwari, S. Nageswari, R. Palanisamy, B. Karthikeyan, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Ali M. El‐Rifaie, Ezzeddine Touti, Ahmed I. Omar

“…The fixed forgetting factor RLS (FFRLS) algorithm is implemented with two different forgetting factor (FF) values, while the VFFRLS method utilizes different initial FF values. …”
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Training multi-layer binary neural networks with random local binary error signals by Luca Colombo, Fabrizio Pittorino, Manuel Roveri

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Sum Rate Maximization of Active RIS-Assisted FD-NOMA Systems by Yi Peng, Yang Xiao, Qingqing Yang

“…Additionally, the optimal transmit powers for all uplink users are obtained through an iterative algorithm. …”
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Energy consumption reduction for an ultra-low-cost artificial pancreas using an event-trigger MPC strategy by Jhon E. Goez-Mora, Pablo S. Rivadeneira

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A Day-Ahead Economic Dispatch Method for Renewable Energy Systems Considering Flexibility Supply and Demand Balancing Capabilities by Zheng Yang, Wei Xiong, Pengyu Wang, Nuoqing Shen, Siyang Liao

“…This approach establishes a dual-layer optimized scheduling model. The upper-layer model focuses on the economic efficiency of unit start-up and shut-down, utilizing a particle swarm algorithm to identify unit combinations that comply with minimum start-up and shut-down time constraints. …”
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Bidding strategies for virtual power plants under the electricity-carbon joint market taking into account wind and solar uncertainties by Shuangchi ZHAO, Hong LIN, Haiyun WANG

“…The upper level maximizes the VPP's profit, while the lower level maximizes social welfare in the joint market. …”
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Multi-Objective Vibration Control of a Vehicle-Track-Bridge Coupled System Using Tuned Inerter Dampers Based on the FE-SEA Hybrid Method by Xingxing Hu, Qingsong Feng, Min Yang, Jian Liu

“…Using the vibration acceleration amplitudes of both the rail and track slab as dual control objectives, a multi-objective optimization model is established, and the TID’s optimal parameters are determined using a multi-objective genetic algorithm. …”
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