Predictive models for overall health of hydroelectric equipment based on multi-measurement point output by Liu Dong, Kong Lijun, Song Jinghui, Zhou Yiming

“…By comparing and analyzing the predictive performance, error results, and real-time prediction performance before and after model optimization, it was concluded that the prediction model constructed by SBM, hypersphere algorithm, and LSTM network had an overall average improvement of 23.7% in the prediction precision of 12 parameters, including temperature, vibration frequency, pressure, and lubrication degree, for the optimized upper guide bearing, thrust guide bearing, and water guide bearing systems. …”
Get full text

Robust Tracking Control of Piezoelectric Actuators Using Super-Twisting Sliding Mode With Bouc-Wen Hysteresis Model-Based Enhanced Jaya Algorithm by Nguyen Thi Thu Hang, Nguyen Ngoc Son

“…The Bouc-Wen model, which captures the nonlinear hysteretic behavior of the PZT actuator, is estimated using a modified Jaya algorithm enhanced with Lévy flight distribution (called LeJaya). …”
Get full text

Binary Secretary Bird Optimization Clustering by Novel Fitness Function Based on Voronoi Diagram in Wireless Sensor Networks by Mohammed Abdulkareem, Hadi S. Aghdasi, Pedram Salehpour, Mina Zolfy

“…To address these limitations, we propose the binary secretary bird optimization clustering (BSBOC) method. BSBOC introduces a binary variant of the secretary bird optimization algorithm (SBOA) to handle the discrete nature of CH selection. …”
Get full text

Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Elias Kosmatopoulos

Get full text

A multi-objective optimization approach for the virtual coupling train set driving strategy by Junting Lin, Maolin Li, Xiaohui Qiu

“…Furthermore, the particle swarm optimization (PSO)-based model predictive control (MPC) algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation, with an average increase of 37.7% in tracking accuracy compared to the traditional MPC algorithm.…”
Get full text

Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…To address this issue and guarantee more accurate ET predictions, this study attempts the following: i) to assess the performance of five machine learning (ML) models optimized by the RReliefF algorithm in estimating actual ET values for each month in four Chinese provinces under various agroclimatic conditions; and ii) to select the optimal model based on statistical metrics while minimizing discrepancies between the estimated and actual ET values. …”
Get full text

Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This research endeavors to elucidate the integration of bio-inspired optimization techniques that improve disease diagnostics through deep learning models. …”
Get full text

An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. …”
Get full text

Transport Capacity Maximization in Rail Mass Transit Stations Under Uncertainty by Adrian Fernandez-Rodriguez, Maria Dominguez, Asuncion P. Cucala, Antonio Fernandez-Cardador

“…At the upper level, a genetic algorithm determines the optimal sequence of train services and platform assignments. …”
Get full text

Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Finally, a correlation analysis was conducted to examine the relationships between these features and other significant clinical features.Results: The logistic regression (LR) model was determined to be the optimal machine learning algorithm in this study, achieving an accuracy of 0.64, a precision of 0.45, a recall of 0.72, an F1 score of 0.51, and an AUC of 0.81 in the training set and 0.91 in the testing set. …”
Get full text

A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…The prescriptive model yielded high performance with average <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> values above 0.93 and low RMSE values, demonstrating that the recommended treatments closely matched the optimal solutions. …”
Get full text

Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

“…Furthermore, to enhance the computational efficiency, a parallel solving strategy is developed, based on the column-and-constraint generation algorithm, the alternating optimization procedure, and the progressive hedging algorithm. …”
Get full text

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation by Zhechuan Jin, Jiale Dong, Chengxiang Li, Yi Jiang, Jian Yang, Lei Xu, Ping Li, Zhun Xie, Yulin Li, Dongjin Wang, Zhili Ji

Get full text

APPLYING GRAPH THEORY TO OPTIMIZE PRODUCT DELIVERY ROUTES AND MINIMIZE COSTS IN THE RESTAURANT BUSINESS by Наталія Волосова, Наталія Стеблюк, Наталія Небаба, Олена Юдіна, Максим Корнєєв, Ганна Богородицька

“…Routing algorithms based on graphical description are considered the most optimal analysis method for developing optimal product delivery routes, which helps minimize enterprise costs. …”
Get full text

Preference-based expensive multi-objective optimization without using an ideal point by Peipei Zhao, Liping Wang, Qicang Qiu

“…The Gaussian process model is built on the objective functions. In the model-based optimization, the projection distance with upper confidence bound (UCB) is developed as the fitness of solutions for each subproblem. …”
Get full text

An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
Get full text

Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…While existing models demonstrate improvements in predictive accuracy and optimization effectiveness, challenges remain in model generalization, computational complexity, and real-time adaptability. …”
Get full text

Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy by Miguel Angel Bergero, Pablo Martínez, Patricio Modina, Ricardo Hosman, Wenceslao Villamil, Romina Gudiño, Carlos David, Lucas Costa

Get full text

A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…The proposed model employs an improved Squirrel Search Algorithm-based Feature Selection (ISSA-FS) to identify the most relevant features from medical data. …”
Get full text

BERT Mutation: Deep Transformer Model for Masked Uniform Mutation in Genetic Programming by Eliad Shem-Tov, Moshe Sipper, Achiya Elyasaf

“…We introduce BERT mutation, a novel, domain-independent mutation operator for Genetic Programming (GP) that leverages advanced Natural Language Processing (NLP) techniques to improve convergence, particularly using the Masked Language Modeling approach. …”
Get full text