Method of Diagnostics of Operation Modes of Individual Heat Supply Units, Allowing to Detect Pre-Emergency Situations at an Early Stage by Dvortsevoy A.I., Borush O.V., Khoreva V.A., Yakovina I.N.

“…This was confirmed by the "Elbow Method", which determined the optimal number, which made it possible to significantly improve the forecasting of emergency modes. …”
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Finding Radial Network Configuration of Distribution System Based on Modified Symbiotic Organisms Search by Thuan Thanh Nguyen, Thanh-Quyen Ngo, Thanh Long Duong, Thang Trung Nguyen

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Features of single treasury account management in the context of budget funds liquidity management by N. S. Sergienko

“…Successful examples of integration of automated financial flow management systems, use of machine learning algorithms for forecasting and optimization of balances on single treasury account, as well as the interdepartmental interaction mechanisms to improve transparency and efficiency of budget management have been considered. …”
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Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method by Mehdi Noormohamadian, Eysa Salajegheh

“…Nowadays, the neural network algorithm is one of the most famous numerical methods for optimizing hull shapes. …”
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Robust fuzzy dynamic integrated environmental-economic-social scheduling considering demand response and user’s satisfaction with electricity under multiple uncertainties by Hong Zhang, Qianwei Xi, Lei Chen, Yong Min, Xiongxiong Fan, Wenjin Fang, Nan Tian, Fei Xu

“…Taking the lowest comprehensive operation cost as the economic objective, the smallest emissions of CO2 and atmospheric pollutants as environmental objective and the largest user’s comprehensive satisfaction with electricity as the social objective, based on the robust fuzzy theory, the multi-objective uncertainty optimal scheduling model is constructed, which is transformed into deterministic model and then solved by intelligent optimization algorithm. …”
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A Full-Profile Measurement Method for an Inner Wall with Narrow-Aperture and Large-Cavity Parts Based on Line-Structured Light Rotary Scanning by Zhengwen Li, Changshuai Fang, Xiaodong Zhang

“…Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. …”
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Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks by Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai

“…To achieve this goal, we formulate the model partitioning problem among heterogeneous hardware and introduce a hierarchical searching algorithm to solve the optimization problem. Besides, a mixed-precision pipeline method is used to reduce the cost of inter-cluster communications. …”
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Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
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Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). …”
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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
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Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

“…By evaluating performance of several regression algorithms using various metrics, this study identifies the most effective method for analyzing sectoral energy consumption. …”
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Threat analysis model to control IoT network routing attacks through deep learning approach by K. Janani, S. Ramamoorthy

“…A deep learning hybrid model based on a Long-Short-Term Memory (LSTM) network and adaptive Mayfly Optimization Algorithm (LAMOA) was presented for the classification of IoT attacks. …”
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Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

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Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

“…Finally, the proposed algorithm is applied to a post-disaster rescue scenario, where the task allocation results further demonstrate its superior performance.…”
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Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning by Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu

“…However, the hyperparameters of the deep learning, which significantly impact the feature extraction and prediction performance, are determined based on expert experience in most cases. The grid search method is introduced in this paper to optimize the hyperparameters of the proposed aircraft engine RUL prediction model. …”
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Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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Research on Control System for Material Transport Vehicle Based on Stacking Model by LIU Yuanming, TANG Lingsi, Zen Shuhua

“…Finally, the control system was reinforced using an improved proportional-integral-differential (PID) control algorithm to optimize the control performance. …”
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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…Additionally, a custom ranking algorithm was designed to identify the most suitable recipients. …”
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Battery swapping scheduling for electric vehicles: a non-cooperative game approach by Yu Zhang, Tao Han, Wei He, Jianhua Xia, Lichao Cui, Zuofu Ma, Shiwei Liu

“…Therefore, it is crucial to develop efficient battery-swapping scheduling algorithms to optimize the operations of battery-swapping systems. …”
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Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations by Min-Hwa Choi, Woongchang Yoon

“…The XGBoost Regressor (XGBR) is optimized using genetic-algorithm-based hyperparameter tuning, reducing mean squared error (RMSE) from 20.9531 to 19.6387, mean absolute error (MAE) from 13.6821 to 12.6753, and improving coefficient of determination (R2) from 0.2791 to 0.2949. …”
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