IoT-Based Traffic Prediction for Smart Cities by Zhinong Miao, Qilong Liao

“…The study suggests that integrating advanced machine learning techniques like CNNs and PSO can lead to more efficient and adaptive traffic management solutions, contributing to the development of smarter, more resilient urban environments. …”
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Kriging-Based Variable Screening Method for Aircraft Optimization Problems with Expensive Functions by Yadong Wang, Xinyao Duan, Jiang Wang, Jin Guo, Minglei Han

“…Therefore, performing variable selection to identify influential inputs becomes crucial for minimizing the number of necessary model evaluations, particularly when dealing with complex systems exhibiting nonlinear and poorly understood input–output relationships. …”
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Multi-dimensional water quality indicators forecasting from IoT sensors: A tensor decomposition and multi-head self-attention mechanism. by Li Bo, Lv Junrui, Luo Xuegang

“…To overcome these limitations, we propose TGMHA (Tensor Decomposition and Gated Neural Network with Multi-Head Self-Attention), a novel hybrid model that integrates three key innovations: 1) Tensor-based Feature Extraction: We combine Standard Delay Embedding Transformation (SDET) with Tucker tensor decomposition to reconstruct raw time series into low-rank tensor representations, capturing latent spatio-temporal patterns while suppressing sensor noise. 2) Multi-Head Self-Attention for Inter-Indicator Dependencies: A multi-head self-attention mechanism explicitly models complex inter-dependencies among diverse water quality indicators (e.g., pH, dissolved oxygen, conductivity) via parallel feature subspace learning. 3) Efficient Long-Term Dependency Modeling: An encoder-decoder architecture with gated recurrent units (GRUs), optimized by adaptive rank selection, ensures efficient modeling of long-term dependencies without compromising computational performance. …”
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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…OBJECTIVES: This study aims to establish a machine learning-based Intelligent Distribution Network (IDN) online topology recognition model to address the limited measurement equipment in distribution networks and improve the accuracy and efficiency of network topology recognition. METHODS: First, light GBM was used for feature selection to reduce computational complexity and improve learning efficiency. …”
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Forecasting Tunnel-Induced Ground Settlement: A Hybrid Deep Learning Approach and Traditional Statistical Techniques With Sensor Data by Syed Mujtaba Hussaine, Linlong Mu, Yimin Lu, Syed Sajid Hussain

“…The proposed DL models, Convolutional Long Short-Term Memory (Conv-LSTM2D) and Convolutional Gated Recurrent Unit (Conv-GRU2D), extend traditional LSTM and GRU architectures with 2D convolutional mechanisms to capture complex spatiotemporal dependencies. Additionally, the statistical Autoregressive Integrated Moving Average (ARIMA)/Seasonal ARIMA (SARIMA) models were enhanced through seasonality removal, automated model selection using the auto_arima algorithm, and parameter fine-tuning via grid search to improve their predictive accuracy. …”
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Research on a Point Cloud Registration Method Based on Dynamic Neighborhood Features by Xinrui Liu, Rutao Wang, Zongsheng Wang

“…This paper introduces a method that can enhance the accuracy and efficiency of point cloud data registration. This method selects the centroid of the point cloud as the feature point and uses the projected distance of this feature point within the dynamic neighborhood to other points as the feature information. …”
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Network Security Situational Awareness Based on Improved Particle Swarm Algorithm and Bidirectional Long Short-Term Memory Modeling by Peng Zheng, Yun Cheng, Wei Zhu, Bo Liu, Shuhong Liu, Shijie Wang, Jinyin Bai

“…The refined Particle Swarm Optimization algorithm is applied to optimize the parameters of the BiLSTM network, enabling a rapid convergence and enhancing the training efficiency, thus effectively identifying the categories of network attacks. …”
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Conductivity Measurement for Non-Magnetic Materials Using Eddy Current Method with a Novel Simplified Model by Changli Yan, Jun Bao, Xuyang Zheng

“…However, conventional ECT is significantly influenced by the thickness of the material, often resulting in the arbitrary selection of excitation frequency. In addition, complex inverse calculations in the eddy current analytical model pose challenges for practical application. …”
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Frequency-informed transformer for real-time water pipeline leak detection by Fengnian Liu, Ding Wang, Junya Tang, Lei Wang

“…Existing leak detection methods often face challenges, such as heavily relying on the manual selection of frequency bands or complex feature extraction, which can be both labour-intensive and less effective. …”
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Methods and effective algorithms for solving multidimensional integral equations by A. B. Samokhin

“…When using a uniform grid, the dimensionality of SLAEs can be several orders of magnitude higher; however, in this case, it may be difficult to describe the complex configuration of the domain. Selection of the particular method depends on the specific problem and available computational resources. …”
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Hybrid deep learning optimization for smart agriculture: Dipper throated optimization and polar rose search applied to water quality prediction. by Amal H Alharbi, Faris H Rizk, Khaled Sh Gaber, Marwa M Eid, El-Sayed M El-Kenawy, Ehsan Khodadadi, Nima Khodadadi

“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Thermal Engineering Tests of Heating Boiler Houses when Working on Peat Fuel by V. K. Lyubov, D. G. Chukhchin, A. N. Popov

“…The conversion of heat generating plants to peat fuel combustion makes it possible to achieve a significant reduction in emissions of solid and soot particles without upgrading ash-collecting plants. Complex experimental studies conducted of existing hot water boilers with a nominal heating capacity of 0.4 and 2.0 MW have shown the possibility, as well as the energy-environmental efficiency of burning briquetted and sod peat in the combustion chambers of these heat generating plants.…”
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ATHEMATICAL MODEL FOR THE OPTIMISATION OF HIERARCHICAL MULTI-LEVEL PRODUCTION SYSTEMS by Yu. V. Minaeva

“…It is possible to use the model’s multi-level unification and scalability to increase modelling efficiency and thus optimise complex multinomenclature productions.…”
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Review on development and utilization of offshore renewable energy: An analysis based on a five-dimensional framework by DU Wenjie, CAI Guotian, Qi Xiaoling, WANG Peng, ZHANG Jixiang

“…However, it also faces challenges such as complex environmental conditions, low reliability, and spatial competition. …”
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A Study on the Yield Stability of Oilseed Sunflower Genotypes under Drought Stress by Nasrin Akbari, Reza Darvishzadeh

“…Based on this, several methods have been introduced for selection with optimal efficiency and high accuracy. …”
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Economic Model Predictive Control for Wastewater Treatment Processes Based on Global Maximum Error POD-TPWL by Zhiyu Wang, Jing Zeng, Jinfeng Liu

“…These advancements underscore the method’s potential for real-time implementation in complex industrial systems, balancing computational efficiency with control precision. …”
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The integration of compressive sensing and clustering for date gathering in unmanned aircraft system–aided networks by Xiangmao Chang, Quan Wang, Zhiguo Qu, Yanchao Zhao

“…Evaluations based on real data traces show that the proposed algorithms greatly reduced the energy consumption of sensor nodes efficiency.…”
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Hybrid Deep Learning Approaches for Improved Genomic Prediction in Crop Breeding by Ran Li, Dongfeng Zhang, Yanyun Han, Zhongqiang Liu, Qiusi Zhang, Qi Zhang, Xiaofeng Wang, Shouhui Pan, Jiahao Sun, Kaiyi Wang

“…Genomic selection plays a crucial role in breeding programs designed to improve quantitative traits, particularly considering the limitations of traditional methods in terms of accuracy and efficiency. …”
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DEVELOPMENT OF PERSPECTIVE ORGANO-HYBRID COMPOSITION BASED ON MODIFIED POLYACRYLONITRILE DURING REPAIR AND INSULATION OPERATIONS IN WELLS by A. S. Gumerova, R. N. Yakubov, L. E. Lenchenkova, D. A. Ilash

“…Introduction: Due to the entry of most of the fields into the final stage of development, the relevance of issues related to improving the efficiency of repair and insulation operations (RIO) conducted at the complicated well stock increases. …”
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Analytical approach to digital channel performance optimization of mobile money transactions in emerging markets by Adeolu Dairo, Krisztián Szűcs

“…The results indicated that fuzzy c-means clustering and RFM algorithm are efficient for target selection. Also, the mapping of clusters with the appropriate channel of transactions revealed that mobile money users’ transactions could be optimized along the digital channel. …”
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