Model order reduction of boiler system using nature-inspired metaheuristic optimization of PID controller by Anurag Singh, Shekhar Yadav, Nitesh Tiwari, Dinesh Kumar Nishad, Saifullah Khalid

“…This study proposes a dual-stage optimization framework that integrates balanced truncation-based model order reduction with nature-inspired metaheuristic algorithms for PID controller tuning to address these issues. …”
Get full text

Enhancing Power Efficiency in 4IR Solar Plants through AI-Powered Energy Optimization by S. Boobalan, TR. Kalai Lakshmi, Shubhangi N. Ghate, Mohammed Hameeduddin Haqqani, Sushma Jaiswal

“…The AI-powered system relies on intelligent algorithms to identify the most efficient energy sources for the industry’s needs and adjust them accordingly while learning from every task it is given. …”
Get full text

Process Optimization for Complex Product Assembly Workshops with AGV Integration via Discrete Event Simulation by Hailong Song, Shengluo Yang, Shuoxin Yin, Zhigang Xu

“…This model simulates the coordination between AGVs and workstations while optimizing workstation layout and material flow. …”
Get full text

Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…Since many devices are battery-powered, choosing the right communication interface is critical for optimizing energy efficiency. Our primary objective is to improve network performance while extending its operational lifespan by identifying an optimal set of interfaces that balance power consumption and efficiency. …”
Get full text

A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…However, the efficiency of these applications depends on optimizing video compression parameters to maintain high detection accuracy while minimizing bandwidth usage and computational costs. …”
Get full text

Machine learning and thermodynamic modeling for optimizing hydrogen production via algae-biomass co-gasification by Thanadol Tuntiwongwat, Takashi Yukawa, Thongchai Rohitatisha Srinophakun, Kanit Manatura, Somboon Sukpancharoen, Seyedali Mirjalili

“…This study pioneers the integration of algae-biomass co-gasification with six ML algorithms to optimize H2 production and syngas quality through comprehensive thermodynamic modeling and artificial intelligence (AI). …”
Get full text

Utilizing Artificial Intelligence (AI) for the optimal design of geothermal cogeneration systems in zero energy building by Ehsanolah Assareh, Mohammad Zoghi, Ali Zare, Hassan Bazazzadeh, Adnan Alboghobeysh, Saleh Mobayen, Nima Izadyar, Siamak Hoseinzadeh

“…Modeling was conducted using the widely recognized EES software, while system optimization employed a combination of neural networks and intelligent optimization algorithms. …”
Get full text

Prediction of Psychoacoustic Metrics Using Combination of Wavelet Packet Transform and an Optimized Artificial Neural Network by Mehdi POURSEIEDREZAEI, Ali LOGHMANI, Mehdi KESHMIRI

“…The proposed method extracts objective psychoacoustic metrics including loudness, sharpness, roughness, and tonality from sound samples, by using a special selection of multi-level nodes of the WPT combined with a trained ANN. The model is optimized using the particle swarm optimization (PSO) and the back propagation (BP) algorithms. …”
Get full text

Incremental GA-Based 3D Trajectory Optimization for Powered Parachute Aerial Delivery Systems by Hanafy M. Omar, Ayman Hamdy Kassem

“…A six-degrees-of-freedom (6-DOF) dynamic model of the PPC is developed, complemented by a novel optimization technique called Incremented Genetic Algorithms (IGA). …”
Get full text

Optimizing resource allocation in remote healthcare via blockchain-enabled decentralized networks and spectral clustering by A. Kanimozhi, K. Vidya

“…The proposed system utilizes the InterPlanetary File System (IPFS) to handle resource requests transparently and securely, while spectral and agglomerative clustering algorithms are employed to optimize delivery routes. …”
Get full text

Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control by Abroon Jamal Qazi, Clarence W. de Silva, Afzal Khan, Muhammad Tahir Khan

“…It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. …”
Get full text

Shape optimization using a level set based mesh evolution method: an overview and tutorial by Dapogny, Charles, Feppon, Florian

“…This article revolves around a recent numerical framework for shape and topology optimization, which features an exact mesh of the shape at each iteration of the process, while still leaving the room for an arbitrary evolution of the latter (including changes in its topology). …”
Get full text

Efficient Resource Allocation for Blockchain-Enabled Mobile Edge Computing: A Joint Optimization Approach by Moein Valitabar, Mohammad Fathi, Keivan Navaie

“…Leveraging these insights, we develop two low-complexity algorithms, which utilizes a greedy assignment strategy for MTs to ESs, and optimally allocates computational frequencies within the MEC and blockchain components. …”
Get full text

Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

“…Traditional optimization techniques, such as genetic algorithms, particle swarm optimization, and ant colony optimization, have demonstrated adaptability in node placement but struggle with real-time self-learning capabilities, requiring frequent retraining to handle continuously changing conditions. …”
Get full text

Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…Meta-heuristic algorithms offer an alternative to traditional gradient-based optimizers for improving DNNs performance. …”
Get full text

Secrecy-Constrained UAV-Mounted RIS-Assisted ISAC Networks: Position Optimization and Power Beamforming by Weichao Yang, Yajing Wang, Dawei Wang, Yixin He, Li Li

“…To address this non-convex, multivariate, and coupled problem, we decompose it into three subproblems, which are solved iteratively using particle swarm optimization (PSO), semi-definite relaxation (SDR), majorization–minimization (MM), and alternating direction method of multipliers (ADMM) algorithms. …”
Get full text

Optimization of Cleaning and Hygiene Processes in Healthcare Using Digital Technologies and Ensuring Quality Assurance with Blockchain by Semra Tebrizcik, Süleyman Ersöz, Elvan Duman, Adnan Aktepe, Ahmet Kürşad Türker

Get full text

Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
Get full text

Risk−Based Cost−Benefit Optimization Design for Steel Frame Structures to Resist Progressive Collapse by Feng Guo, Xuancen Li, Aiyan Xu, Yuchen Zhang, Wanping Pan

“…The elements’ cross-section design for the progressive collapse resistance of steel frame structures is optimized using genetic algorithms and SAP2000 23, which identify the structural model with the minimum robustness index while ensuring safety. …”
Get full text

Interpretability-Oriented Adjustment of K-Means: A Multiple-Objective Particle Swarm Optimization Framework by Liang Chen, Leming Sun, Caiming Zhong

“…Subsequently, the model utilizes a multi-objective optimization framework to optimize the three objective functions in the solution space formed by different feature subspaces, resulting in a set of Pareto solutions. …”
Get full text