Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction by Jose Daniel Cuellar Lobo, Zhen Lei, Hexu Liu, Hong Xian Li, SangHyeok Han

“…The integration of BIM with other analytical algorithms also allows optimization of designs, such as the generative design that can parametrize the design. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…In addition, we propose the MDBO-BP-Adaboost model to predict students' performance. Firstly, the model incorporates the good point set initialization, triangle wandering strategy and adaptive t-distribution strategy to obtain the Modified Dung Beetle Optimization Algorithm (MDBO), secondly, it uses MDBO to optimize the weights and thresholds of the BP neural network, and lastly, the optimized BP neural network is used as a weak learner for Adaboost. …”
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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

“…Accurate crop yield prediction is crucial for formulating agricultural policies, guiding agricultural management, and optimizing resource allocation. This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. …”
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Inversion Study of Hydrogeological Parameters for Metro Foundation Pit Confined Aquifiers Based on Surrogate Modeling by YE Ru, DI Honggui, ZHU Zhitai, ZHU Yilong, JIANG Bin, XIANG Longsheng, CHAI Dongsheng, YAO Qiyu

“…The use of deep learning-based surrogate modeling combined with optimization algorithms enables efficient and accurate inversion analysis of groundwater parameters.…”
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A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

“…Sparsity is a highly desired feature in deep neural networks (DNNs) since it ensures numerical efficiency, improves the interpretability (due to the smaller number of relevant features), and robustness. …”
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Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

“…The dual-algorithm approach provided improved detection capabilities compared to traditional methods, underscoring its potential for scalable and effective cybersecurity applications. …”
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A novel and efficient personalized stress detection technique using a deep learning model by Ulligaddala Srinivasarao, Gopisetty Rathnamma, M. Satish Kumar, Lakshmipathi Anantha, Rakesh Kumar Donthi, T. Jhansi Rani

“…The Chaotic Fennec Fox Optimization Algorithm (CFFO) tunes the hyperparameter. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Initially, the SIMDP-EDLIoT approach uses linear scaling normalization (LSN) to ensure that the input data is scaled appropriately. Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
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Exponential Squared Loss-Based Robust Variable Selection with Prior Information in Linear Regression Models by Hejun Wei, Tian Jin, Yunquan Song

“…Experimental results demonstrate that our model significantly improves estimation robustness compared to existing methods, even in outlier-contaminated scenarios.…”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…Our research in Mahanadi River Basin, Odisha, presents an enhanced methodology based on data, specifically designed to be beneficial for Water Quality (WQ) based on Synthetic Pollution Index (SPI) and machine learning models such as Long Short-Term Memory (LSTM) and Sparrow Search Algorithm (SSA), for its analysis and interpretation of extensive, intricate data sets on water quality, as well as the allocation of pollution sources or contributing elements, in order to improve knowledge of the water quality and the planning of monitoring networks for efficient water resource management. …”
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Data-driven seismic mechanical performance evaluation of RC columns based on adaptive optimization ensemble learning method integrating random forest and back propagation neural ne... by Ayong Jiao, Ziqing Jiao, Bin Gao

“…An improved black-winged kite optimization algorithm (IBKA), based on Levy flight and adaptive t-distribution strategies, is used to optimize the hyperparameters of the base models. …”
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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

“…In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency improvements, and resource allocation. This paper examines the application of artificial intelligence and supervised machine learning techniques to modeling and predicting the energy consumption patterns in the smart grid sector of a commercial building located in Singapore. …”
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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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Dimensionless analysis and novel configuration for enhanced natural convection cooling in lithium-ion batteries by Congyu Mao, Min Liang Wang, Kewei Gao, Hongdi Jin, Woo Young Cho, Hernando Leon-Rodriguez, Kootaek Hong, Seunghwoi Han, Jihoon Jeong, Hyun Wook Kang

“…A dimensionless analysis framework was developed and coupled with response surface models and a multi-objective genetic algorithm to optimize battery layouts for heat dissipation and temperature uniformity. …”
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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

“…This study aims to develop an intelligent solution for predicting student performance using supervised machine learning algorithms. This proposed focus on addressing the limitations of existing prediction models and enhancing prediction accuracy. …”
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Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification by Zuojun Zheng, Jianghao Yuan, Wei Yao, Paul Kwan, Hongxun Yao, Qingzhi Liu, Leifeng Guo

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Quantum-enhanced digital twin IoT for efficient healthcare task offloading by Ahmed K. Jameil, Hamed Al-Raweshidy

“…Empirical evaluations show that quantum preprocessing improved Task Offloading Success Rate (TOSR) by 32% and reduced the Error Rate (ER) by 80%, significantly outperforming traditional DT-based healthcare models. …”
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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…In addition, the Cross-Validation Grid Search Algorithm (GSA) was used to optimize the hyperparameters to ensure that the model can achieve the optimal performance on different data sets. …”
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Multimodal Control by Variable-Structure Neural Network Modeling for Coagulant Dosing in Water Purification Process by Jun Zhang, Da-Yong Luo

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Comparative analysis and selection of the geometry of the microphone array based on MEMS microphones for sound localisation by Andrii Riabko, Tetiana Vakaliuk, Oksana Zaika, Roman Kukharchuk, Yuriy Smorzhevsky

“…The subject of this article is the design and optimization of the geometric configuration of omnidirectional MEMS microphone arrays for sound localization tasks. …”
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