A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…Additionally, the hybrid approach enables early predictions of approximately 17 cycles and late predictions of only 2%, while other learning algorithms, such as linear regression, do not make early predictions but 100% of their predictions are late. …”
Get full text

Novel Application of Quantum Computing for Routing and Spectrum Assignment in Flexi-Grid Optical Networks by Oumayma Bouchmal, Bruno Cimoli, Ripalta Stabile, Juan Jose Vegas Olmos, Carlos Hernandez, Ricardo Martinez, Ramon Casellas, Idelfonso Tafur Monroy

“…By formulating the problem as a Quadratic Unconstrained Binary Optimization (QUBO) model, we employ the Quantum Approximate Optimization Algorithm (QAOA) to effectively solve it. …”
Get full text

The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. …”
Get full text

A novel Parrot Optimizer for robust and scalable PEMFC parameter optimization by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Gulothungan G., Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…I–V and V–P characteristic simulations match experimental results across different temperature and pressure values which proves the theoretical value and practical usage of PO in solving nonlinear optimization problems. The study demonstrates PO as a dependable optimization method which improves PEMFC design processes while enhancing operational reliability through future research that includes real-time control and algorithm combination and system scalability.…”
Get full text

A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Hence, a novel hybrid model is provided, incorporating singular value decomposition (SVD) in conjunction with kernel-based ridge regression (SKRidge), multivariate variational mode decomposition (MVMD), and the light gradient boosting machine (LGBM) as a feature selection method, along with the Runge–Kutta optimization (RUN) algorithm for parameter optimization. …”
Get full text

Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
Get full text

Aerodynamic Optimization of Morphing Airfoil by PCA and Optimization-Guided Data Augmentation by Ao Guo, Jing Wang, Miao Zhang, Han Wang

“…A Multi-Island Genetic Algorithm (MIGA) efficiently explores the reduced design space, while iterative retraining of the surrogate model enhances prediction accuracy, particularly in high-performance regions. …”
Get full text

Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
Get full text

Efficient Frequency Management for Hybrid AC/DC Power Systems Based on an Optimized Fuzzy Cascaded PI−PD Controller by Awadh Ba Wazir, Sultan Alghamdi, Abdulraheem Alobaidi, Abdullah Ali Alhussainy, Ahmad H. Milyani

“…The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. …”
Get full text

Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. …”
Get full text

Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
Get full text

Double layered expansion planning for virtual power plants considering virtual energy storage systems by Jianghai Ma, Xuanwen Gu, Yao Zhang, Jinming Gu, Wenjie Luo, Feng Gao

“…To improve computational efficiency, a hybrid Grey Wolf Optimization algorithm is employed for model solution. …”
Get full text

Mitigating Dead Node Impact on Coverage and Connectivity in Wireless Sensor Networks Using a Hybrid Approach by Omeed K. Khorsheed

“…The ABC algorithm adjusts sensor node placement to maximize the coverage and minimize holes, while the SRCA algorithm restores connectivity by reconnecting the network when nodes fail. …”
Get full text

Energy management for microgrids integrating renewable sources and hybrid electric vehicles by Wanying Liu, Chunqing Rui, Zilin Liu, Jinxin Chen

“…It also incorporates demand response mechanisms for greater resilience. The Kepler Optimization Algorithm (KOA), inspired by Kepler's laws of planetary motion, is employed to tackle the nonlinear optimization problem. …”
Get full text

A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…Experimental findings indicate that the P-BTLBO algorithm surpasses conventional optimization methods, including TLBO and PSO, regarding classification accuracy, feature subset size, and computational efficiency. …”
Get full text

A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

Get full text

The Equal-Time Waypoint Method: A Multi-AUV Path Planning Approach That Is Based on Velocity Variation by Chenxin Yin, Kai Shi, Hailong Wang

Get full text

An improved catastrophe progression method based on HMSLGWO–AHP for grouting quality assessment by Yushan Zhu, Zhu Yang, Ning Li, Jian Huang

“…Subsequently, the analytic hierarchy process (AHP) method improved by the hierarchical multi‐strategy learning gray wolf optimization (HMSLGWO) algorithm is employed to determine the relative significance of indices, in which, the HMSLGWO algorithm, augmented by Gaussian mixture model clustering and multi‐strategy learning, optimizes the consistency of the AHP judgment matrix. …”
Get full text

An overview of distributed economic dispatch of microgrids: advances and challenges by Lei Sun, Wenjing An, Yangkai Chen, Peifeng Zhao, Derui Ding

“…Economic dispatch (ED) is necessary to achieve optimal power allocation while meeting practical physical constraints and ensuring economic benefits and production safety. …”
Get full text

WSNetDefender: Securing Wireless Sensor Networks Using BBIDNet and Fuzzy-DQN Threat Mitigation System (FD-TMS) by Mohammed A. Aleisa

Get full text