Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…This study proposes an Osprey Optimization Algorithm with Deep Learning Assisted Crowd Density Detection and Classification (OOADL-CDDC) technique for smart video surveillance systems. …”
Get full text

A Comprehensive Analysis of the Triple-Hybrid Metamodel of MLP-PSO-ARIMA for Forecasting the FDSD Index: A Case Study of Khuzestan Province by Mohammad Ansari Ghojghar

Get full text

Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and... by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Unlike traditional data acquisition methods, this approach enables a methodical and structured exploration of adsorption behavior while reducing the number of required experiments, leading to improved prediction accuracy, optimization, and cost-effectiveness. …”
Get full text

Sample-Adjusted Threshold Calculation (SATC) for Optimizing Flood Mapping From a Trustworthy and Explainable Perspective by Zhijun Jiao, Biyan Chen, Zhimei Zhang, Lixin Wu

“…The experimental results of applying SATC to various scenarios indicate that these SATC-optimized algorithms achieve a notable 10–30% improvement in accuracy while concurrently reducing false and omission rates to <20% . …”
Get full text

Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease by Saif Wali Ali Alsudani, Ghassan Khudair Saud

“… Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of speech-based signals. …”
Get full text

Multi-clause deduction algorithm based on dynamic combination optimization of strategies and its application(策略动态组合优化多元演绎算法及应用) by 郭海林(GUO Hailin), 曹锋(CAO Feng), 易见兵(YI Jianbing), 李俊(LI Jun), 吴贯锋(WU Guanfeng)

“…In order to better guide the clause selection in multi-clause deduction, multi-clause deduction method based on dynamic combination optimization of strategies is proposed. This method dynamically combines and iteratively optimizes the number of words and function term depth of clause, fully exploring the existing multi-clause deduction heuristic strategies while improving the adaptability of different problems to strategies, achieving efficient clause selection of multi-clause deduction. …”
Get full text

Disturbance Observer-Based Bio-Inspired LQR Optimization for DC Motor Speed Control by Mubarak Badamasi Aremu, Mohammed Abdel-Nasser, Nezar M. Alyazidi, and Sami El-Ferik

“…Numerous simulations demonstrate the enhanced performance of the developed technique in achieving optimal speed control while maintaining high robustness.…”
Get full text

Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…To enhance model performance, the slime mould algorithm is employed for parameter optimization. Experimental results demonstrated that the hybrid model achieves excellent predictive accuracy, with crop yield prediction exceeding 99%. …”
Get full text

Program Scheduling With Multi-Skill and External Resource Coordination Consideration Using Improved NSGA-II: Case Study by Heng Zhang, Jingbo Zhou, Huaying Ruan, Yixuan Qin

“…The allocation model was solved using both the classic and improved versions of the algorithm. The outcomes indicate that the fitness of the final generation significantly exceeds that of the initial generation, and the refined algorithm outperforms the conventional one in reducing the project duration and enhancing balance, with the potential to reduce project duration by 9% and enhance the balance by 40%. …”
Get full text

Machine-learning based optimizing the neutronic and thermal-hydraulic performance in a VVER-1000 mixed-core as well as fuel burnup assessment by A. Koraniany, G.R. Ansarifar

“…By integrating this neural network with a genetic algorithm, optimization was carried out to identify the optimal fuel placement and enrichment for loading the UTVS fuel assembly into the targeted reactor core. …”
Get full text

Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms by Claudio Cicconetti

“…While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. …”
Get full text

Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
Get full text

Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques by Saksham Anand, Venkatachalam Gopalan, Shenbaga Velu Pitchumani

“…To address these challenges, the study uses Response Surface Methodology (RSM) and three nature-inspired optimization methods viz. Particle Swarm Optimization (PSO), Dragonfly Optimization (DFO) and Cuckoo Search Algorithm (CSA) to improve factors like fibre content, particle size and chemical treatment. …”
Get full text

A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
Get full text

An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system by Ivan V. Stepanyan, Safa A. Hameed

Get full text

A Framework for Multi-Objective Optimization in Energy Retrofit of Heritage Museums: Enhancing Preservation, Comfort, and Conservation Conditions by Camila Gea-Salim, Silvana Flores-Larsen, Marcos Hongn, Silvina Gonzalez

Get full text

Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy by T. Yuvaraj, T. Sengolrajan, Natarajan Prabaharan, K. R. Devabalaji, Akie Uehara, Tomonobu Senjyu

“…A hybrid improved grey wolf optimization-particle swarm optimization (IGWO-PSO) algorithm is developed to solve this complex optimization problem. …”
Get full text

A constructal theory framework for optimizing HRSG design: Enhancing thermal performance and cost-effectiveness by Morteza Mehrgoo, Majid Amidpour

“…Thermal efficiency improvements facilitate a 7.3-9.8% increase in steam production while maintaining optimal pinch point temperature differences of 10-12°C. …”
Get full text

The Mode of Constructing Safe Trajectories of Motion of the Unmanned Aerial Vehicle while Monitoring Power Lines Considering the Influence of their Electromagnetic Fields by Shabanova A.R., Tolstoy I.M., Lebedev I.V.

Get full text

Smart homes energy management: Optimal multi-objective appliance scheduling model considering electrical energy storage and renewable energy resources by Moslem Dehghani, Seyyed Mohammad Bornapour

“…The maximum standard deviation of total objective function between all cases for IBBO, gray wolf optimizer (GWO), and whale optimization algorithm (WOA) are 6.55, 17.22, and 24.87, respectively, which show the robustness of IBBO in finding the best solution in comparisons of other algorithms. …”
Get full text