Enhancing HVAC Control Systems Using a Steady Soft Actor–Critic Deep Reinforcement Learning Approach by Hongtao Sun, Yushuang Hu, Jinlu Luo, Qiongyu Guo, Jianzhe Zhao

“…Specifically, we introduce cumulative returns into the SAC framework and recalculate target values, which reduces the loss function. The proposed HVAC control algorithm achieved 24.2% energy savings compared to the baseline SAC algorithm. …”
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Comparative analysis of daily global solar radiation prediction using deep learning models inputted with stochastic variables by Amit Kumar Yadav, Raj Kumar, Meizi Wang, Gusztáv Fekete, Tej Singh

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Advanced machine learning technique for solving elliptic partial differential equations using Legendre spectral neural networks by Ishtiaq Ali

“…In this work, a novel approach based on a single-layer machine learning Legendre spectral neural network (LSNN) method is used to solve an elliptic partial differential equation. …”
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Investigations on higher-order spherical harmonic input features for deep learning-based multiple speaker detection and localization by Nils Poschadel, Stephan Preihs, Jürgen Peissig

“…Abstract In this paper, a detailed investigation of deep learning-based speaker detection and localization (SDL) with higher-order Ambisonics signals is conducted. …”
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A computer vision system and machine learning algorithms for prediction of physicochemical changes and classification of coated sweet cherry by Yashar Shahedi, Mohsen Zandi, Mandana Bimakr

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Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…The Firefly Algorithm (FA), utilizing 5-fold cross-validation as the fitness function, adeptly navigates complex hyperparameter spaces, enhancing model performance across diverse data partitions. …”
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Android malware detection via efficient application programming interface call sequences extraction and machine learning classifiers by Tanjie Wang, Yueshen Xu, Xinkui Zhao, Zhiping Jiang, Rui Li

“…In API call sequences extraction, we propose an algorithm for transforming the function call graph from a multigraph into a directed simple graph, which successfully avoids the unnecessary repetitive path searching. …”
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Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits. by Mohsen Yoosefzadeh-Najafabadi, Dan Tulpan, Milad Eskandari

“…These data were used for predicting the total soybean seed yield using the Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Random Forest (RF), machine learning (ML) algorithms, individually and collectively through an ensemble method based on bagging strategy (E-B). …”
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Predicting age at first calving of dairy breed calves using whale optimization-based ensemble learning framework by Tewodros Shekure, Hussien Seid Worku, Sudhir Kumar Mohapatra, Tapan Kumar Das

“…Second, a model was developed by tuning hyperparameters of SVR including kernel function, regularization (C-parameter) and gamma parameters, and it resulted in an accuracy of 96.46%. …”
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Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…This paper introduces a novel generalisation of message passing into learning-based function approximation, namely multimodal heterogeneous network flow, which models information propagation across different semantic domains under conservation constraints. …”
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Clinical Characterization of Patients with Syncope of Unclear Cause Using Unsupervised Machine-Learning Tools: A Pilot Study by María-José Muñoz-Martínez, Manuel Casal-Guisande, María Torres-Durán, Bernardo Sopeña, Alberto Fernández-Villar

“…The number of clusters was determined through cost function analysis and silhouette index, and visual validation was performed using UMAP. …”
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Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…Despite advancements in both traditional methodologies and modern deep learning models, challenges such as suboptimal accuracy and elevated false alarm rates persist, particularly in complex environmental scenarios. …”
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Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization by Fadiyah M. Almutairi, Sara A. Althubiti, Shabnam Mohamed Aslam, Habib Dhahri, Omar Alhajlah, Nitin Mittal

“…This research aims to develop a deep-learning (DL) tool to detect the AIG from clinical-grade endoscopic images. …”
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Intelligent Energy-Efficient Train Trajectory Optimization Approach Based on Supervised Reinforcement Learning for Urban Rail Transits by Guannan Li, Siu Wing Or, Ka Wing Chan

“…This paper proposes a three-step supervised reinforcement learning-based intelligent energy-efficient train trajectory optimization (SRL-IETTO) approach for iATO by hybrid-integrating deep reinforcement learning (DRL) and supervised learning. …”
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Enhanced People Re-identification in CCTV Surveillance Using Deep Learning: A Framework for Real-World Applications by Mossaab Idrissi Alami, Abderrahmane Ez-zahout, Fouzia Omary

“…In this paper, we propose a robust deep learning framework that leverages convolutional neural networks (CNNs) with a customized triplet loss function to overcome these obstacles and improve re-identification accuracy. …”
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Machine learning and artificial intelligence: Enabling the clinical translation of atomic force microscopy-based biomarkers for cancer diagnosis by Aidan T. O’Dowling, Brian J. Rodriguez, Tom K. Gallagher, Stephen D. Thorpe

“…The influence of biomechanics on cell function has become increasingly defined over recent years. …”
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A Symmetric Projection Space and Adversarial Training Framework for Privacy-Preserving Machine Learning with Improved Computational Efficiency by Qianqian Li, Shutian Zhou, Xiangrong Zeng, Jiaqi Shi, Qianye Lin, Chenjia Huang, Yuchen Yue, Yuyao Jiang, Chunli Lv

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A Novel Trustworthy Toxic Text Detection Method with Entropy-Oriented Invariant Representation Learning for Portuguese Community by Wenting Fan, Haoyan Song, Jun Zhang

“…Meanwhile, we devise a trustworthy text recognition module by defining the Dirichlet function to model uncertainty estimation of text prediction. …”
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On the Sufficiency of a Single Hidden Layer in Feed-Forward Neural Networks Used for Machine Learning of Materials Properties by Ye Min Thant, Sergei Manzhos, Manabu Ihara, Methawee Nukunudompanich

“…Feed-forward neural networks (NNs) are widely used for the machine learning of properties of materials and molecules from descriptors of their composition and structure (materials informatics) as well as in other physics and chemistry applications. …”
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Machine-Learning-Powered Information Systems: A Systematic Literature Review for Developing Multi-Objective Healthcare Management by Maryam Bagheri, Mohsen Bagheritabar, Sohila Alizadeh, Mohammad (Sam) Salemizadeh Parizi, Parisa Matoufinia, Yang Luo

“…The incorporation of machine learning (ML) into healthcare information systems (IS) has transformed multi-objective healthcare management by improving patient monitoring, diagnostic accuracy, and treatment optimization. …”
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