Results 91 to 100 of about 40,966 (267)

Enhancing Power System Flexibility Using AI‐Based Forecasting Techniques: A Comparative Study

Battery Energy, Volume 5, Issue 1, January 2026.
This study compares AI‐based forecasting techniques for enhancing power system flexibility. XGBoost outperforms other models in short‐term load forecasting, enabling more reliable grid management and adaptive energy operations. ABSTRACT This paper compares seven forecasting models for hourly electricity consumption in a commercial office building using
Saad Hayat, Aamir Nawaz, Aftab Ahmed Almani, Ehtasham Mustafa, Zahid Javid, William Holderbaum   +5 more
wiley   +1 more source

Evaluation of the Power Demand for Economic Load Dispatch Problem Using Adaptive Neuro-Fuzzy Inference System and Artificial Neural Network

IEEE Access
The evaluation of power demand is fundamental in the Economic Load Dispatch problem, ensuring that the generated power meets the needs of consumers reliably and efficiently in planning system operations.
Somchat Jiriwibhakorn, Kamolwan Wongwut
doaj   +1 more source

316L Paslanmaz Çeliklerin Frezeleme işlemindeki Yüzey Pürüzlülüğün ANFIS ile Modellenmesi

Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2019
Paslanmaz çelikler, mükemmel korozyon direnci, düşük ve yüksek sıcaklıklarda kullanılabilmesi, kolay şekillendirilebilmesi ve iyi estetik görünüme sahip olmasından dolayı birçok alanda kullanılabilen bir malzemedir.
Yusuf Fedai, Ali Ünüvar, Hediye Kırlı Akın, Gökhan Başar   +3 more
doaj   +1 more source

Optimization and predictive modelling of biodiesel production from waste cooking oil catalyzed by blast furnace slag geopolymer using RSM and machine learning

The Canadian Journal of Chemical Engineering, Volume 104, Issue 1, Page 6-30, January 2026.
Abstract Biodiesel production from waste cooking oil (WCO) has emerged owing to growing interest in sustainable energy sources. Geopolymers synthesized from industrial wastes, such as blast furnace slag (BFS), are promising catalysts because of their environmental benefits and catalytic properties.
Pascal Mwenge, Djemima Bulanga, Hilary Rutto, Tumisang Seodigeng   +3 more
wiley   +1 more source

Fractional order ANFIS controllers for LFC in RES integrated three-area power system

Journal of Electrical Systems and Information Technology
The existing adaptive neuro-fuzzy inference system (ANFIS) for load frequency control in multi-area power systems has two inputs consisting of area control error (ACE) and its integer order derivative.
Yaw O. M. Sekyere, Francis B. Effah, Philip Y. Okyere   +2 more
doaj   +1 more source

Prediction of Ultimate Strain and Strength of FRP-Confined Concrete Cylinders Using Soft Computing Methods

Applied Sciences, 2017
This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering ...
Iman Mansouri, Ozgur Kisi, Pedram Sadeghian, Chang-Hwan Lee, Jong Wan Hu   +4 more
doaj   +1 more source

AI‐Driven Optimization Techniques for Power Quality Improvement in Microgrids: Trends, Techniques, and Future Directions

Energy Science &Engineering, Volume 14, Issue 1, Page 583-610, January 2026.
Decentralized energy systems are gaining momentum, and microgrids have become a vital component of the modern power landscape. Yet, maintaining power quality within these systems presents ongoing challenges due to the presence of nonlinear loads, variable renewable energy sources, and frequent switching operations.
Mahnoor Zahid, Hafiz Mudassir Munir, Mohammad Adeel, Fares Suliaman Alromithy, Mohammad R. Altimania, Ievgen Zaitsev   +5 more
wiley   +1 more source

Research on Annual Runoff Prediction Based on EMD-LSTM-ANFIS Model

Renmin Zhujiang, 2021
To improve the accuracy of runoff prediction,this paper proposes a runoff prediction model based on the combination of empirical mode decomposition (EMD),long short-term memory (LSTM) neural network,and adaptive neuro-fuzzy inference system (ANFIS ...
HU Shunqiang, CUI Dongwen
doaj  

Enhancing Hybrid Microgrid Dynamics Using an Agent‐Based Reinforcement Learning (RL) Framework

Energy Science &Engineering, Volume 14, Issue 1, Page 144-162, January 2026.
Overview of (RL) framework ABSTRACT Hybrid microgrids, integrating renewable, and conventional energy sources are critical for sustainable and resilient power systems. Their dynamic performance is affected by uncertainties in load demand, generation variability, and control strategies.
Sudhakiran Ponnuru, Vendoti Suresh, B. Krishnaveni, Ravindra S., Venkateshmurthy B. S., M. Satyanarayana Gupta, K. Aravinda, M. J. D. Ebinezer, S. Prabhakar   +8 more
wiley   +1 more source

Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO)

Applied Sciences, 2019
The most dangerous landslide disasters always cause serious economic losses and human deaths. The contribution of this work is to present an integrated landslide modelling framework, in which an adaptive neuro-fuzzy inference system (ANFIS) is combined ...
Wei Chen, Haoyuan Hong, Mahdi Panahi, Himan Shahabi, Yi Wang, Ataollah Shirzadi, Saied Pirasteh, Ali Asghar Alesheikh, Khabat Khosravi, Somayeh Panahi, Fatemeh Rezaie, Shaojun Li, Abolfazl Jaafari, Dieu Tien Bui, Baharin Bin Ahmad   +14 more
doaj   +1 more source