LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…The current study introduces an optimization algorithm, Learner Performance-Based Behavior with Simulated Annealing (LPBSA), integrated with Multilayer Perceptron (MLP) as a neural network technique to improve disease prediction accuracy. …”
Get full text

Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration by Ousama M.T. Ajami, Rodney H.G. Tan, Mithulan Nadarajah, Farah Adilah Jamaludin, Adlan Bagus Pradana

“…The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. …”
Get full text

Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm by Juncheng Fu, Zhengxiang Song, Jinhao Meng, Chunling Wu

“…Addressing the non-linear and non-stationary characteristics of battery capacity sequences, a novel method for predicting lithium battery SOH is proposed using a deep hybrid kernel extreme learning machine (DHKELM) optimized by the improved black-winged kite algorithm (IBKA). …”
Get full text

Enhanced hunger games search algorithm that incorporates the marine predator optimization algorithm for optimal extraction of parameters in PEM fuel cells by Mohamed Issa, Mohamed Abd Elaziz, Sameh I. Selem

“…Abstract This article introduces a novel optimization approach to improve the parameter estimation of proton exchange membrane fuel cells (PEMFCs), which are critical for diverse applications but are challenging to model due to their nonlinear behavior. …”
Get full text

Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network by Shaoyang Yin, Zhaohui Chen, Wanyuan Liu, Zhiwen Su

Get full text

Improving the efficiency of frequency regulation for High-Power diesel generators by Shchasiana Arhun, Aleksandr Bogajevskiy, Andrii Hnatov, Nadezhda Kunicina

Get full text

Aquaculture Prediction Model Based on Improved Water Quality Parameter Data Prediction Algorithm under the Background of Big Data by Yuan Jiang, Fei Yan

“…Considering the complex relationship between dissolved oxygen and water quality, combined with principal component analysis, a PCA-BP (principal component analysis back propagation) water quality prediction model was proposed. The parameters of PCA-BP water quality prediction model were optimized by genetic algorithm, the threshold and weight of BP neural network were determined, and an improved PCA-BP water quality prediction model was constructed. …”
Get full text

Fuzzy Fault Tree Maintenance Decision Analysis for Aviation Fuel Pumps Based on Nutcracker Optimization Algorithm–Graph Neural Network Improvement by Weidong He, Xiaojing Yin, Yubo Shao, Dianxin Chen, Jianglong Mi, Yang Jiao

“…Therefore, this paper proposes the NOA (Nutcracker Optimization Algorithm)–GNN (Graph Neural Network) model to enhance the accuracy and robustness of FTA by mitigating the uncertainty and inconsistency in expert knowledge. …”
Get full text

Hidden-layer configurations in reinforcement learning models for stock portfolio optimization by Patrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik Faturohman

“…This study explores the impact of hidden-layer configurations in reinforcement learning models for stock portfolio optimization. Using a portfolio of 45 actively traded stocks in the Indonesian stock market, the performance of four reinforcement learning algorithms—Advantage Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO), and Twin Delayed Deep Deterministic Policy Gradient (TD3)—is evaluated with zero, one, and two hidden layers. …”
Get full text

Optimizing high-speed train tracking intervals with an improved multi-objective grey wolf by Lin Yue, Meng Wang, Peng Wang, Jinchao Mu

“…To achieve multi-objective dynamic optimization, a novel train tracking operation calculation method is proposed, utilizing the improved grey wolf optimization algorithm (MOGWO). …”
Get full text

Donor Segmentation Analysis Using the RFM Model and K-Means Clustering to Optimize Fundraising Strategies by Rezki ., Nouval Trezandy Lapatta, Rizka Ardiansyah, Wirdayanti ., Dwi Shinta Angreni

“…This study aims to segment donors using the Recency, Frequency, Monetary (RFM) model and the K-Means algorithm to optimize fundraising strategies. …”
Get full text

CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model by Li Jie, Wang Shuai, Lan Hai, Wang Zhiyong

“…Compared with the traditional BP model, the prediction accuracy is obviously improved, which can meet the needs of practical engineering. …”
Get full text

Performance Analysis of Battery State Prediction Based on Improved Transformer and Time Delay Second Estimation Algorithm by Bo Gao, Xiangjun Li, Fang Guo, Xiping Wang

“…The Time Delay Second Estimation (TDSE) algorithm optimized the improved Transformer model to overcome traditional models’ limitations in extracting long-term dependency. …”
Get full text

CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…Due to the slow convergence speed and the tendency to fall into local optimal solutions of the Hippopotamus Optimization Algorithm (HO), an improved Hippopotamus Optimization (IHO) algorithm-optimized Support Vector Machine (SVM) model for valve leakage diagnosis is introduced to further enhance the accuracy of valve leakage diagnosis. …”
Get full text

Optimizing a Hybrid Controller for Automotive Active Suspension System by Using Genetic Algorithms With Two High Level Parameters by Vu Van Tan, Do Trong Tu, Nguyen Van Vinh, Pham Tat Thang, Andras Mihaly, Peter Gaspar

“…Subsequently, the coefficients of the HASS are optimized through the Genetic Algorithm optimization with the parameter <inline-formula> <tex-math notation="LaTeX">$\beta =0.1,\,0.5,\,0.9$ </tex-math></inline-formula>, aiming to enhance ride comfort and road holding corresponding to each value of <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>. …”
Get full text

Neurodynamic robust adaptive UWB localization algorithm with NLOS mitigation by Yanxu Liu, Enwen Hu, Yudong Chen, Changyou Guo

“…We proposed an adaptive distance error upper bound method to improve the accuracy of localization model. Tested in representative numerical simulation and real environments, our proposed robust adaptive positioning algorithm outperforms existing methods in terms of localization accuracy and robustness, especially in severe NLOS environments.…”
Get full text

An Optimized Method for Solving the Green Permutation Flow Shop Scheduling Problem Using a Combination of Deep Reinforcement Learning and Improved Genetic Algorithm by Yongxin Lu, Yiping Yuan, Jiarula Yasenjiang, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…It introduces a novel hybrid approach that combines end-to-end deep reinforcement learning with an improved genetic algorithm. Firstly, the PFSP is modeled using an end-to-end deep reinforcement learning (DRL) approach, named PFSP_NET, which is designed based on the characteristics of the PFSP, with the actor–critic algorithm employed to train the model. …”
Get full text

Enhanced anomaly network intrusion detection using an improved snow ablation optimizer with dimensionality reduction and hybrid deep learning model by Fatimah Alhayan, Asma Alshuhail, Ahmed Omer Ahmed Ismail, Othman Alrusaini, Sultan Alahmari, Abdulsamad Ebrahim Yahya, Sami Saad Albouq, Mutasim Al Sadig

“…This manuscript proposes an Enhanced Anomaly Intrusion Detection using an Optimization Algorithm with Dimensionality Reduction and Hybrid Model (EAID-OADRHM) technique. …”
Get full text

An Improved YOLOv9s Algorithm for Underwater Object Detection by Shize Zhou, Long Wang, Zhuoqun Chen, Hao Zheng, Zhihui Lin, Li He

“…We combine the inverted residual structure of MobileNetV2 with Simple Attention Module (SimAM) and Squeeze-and-Excitation Attention (SE) to form the Simple Enhancement attention Module (SME) and optimize AConv, improving the sensitivity of the model to object details. …”
Get full text

An Improved Exact Algorithm for Least-Squares Unidimensional Scaling by Gintaras Palubeckis

“…In this paper, we propose an improved branch-and-bound algorithm for solving this problem. …”
Get full text