SOLAR RADIATION FORECASTING USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS)
Journal Title: Engineering and Technology Journal - Year 2023, Vol 8, Issue 07
Abstract
Hybrid intelligent systems have previously been centered on forecasting solar energy using meteorological data parameters; nevertheless, such forecasting approaches have yielded unreliable results. The goal of this research is to design and develop ANFIS model for forecasting solar energy based on widely shifting environmental factors utilizing experimental data collected in Abuja. This is accomplished by developing a system that predicts solar energy generation using an Artificial Neural Network (ANN) and fuzzy logic. This research examines four Adaptive Neuro Fuzzy Inference System (ANFIS) models that were developed and tested in Abuja, Nigeria, for horizontal sun radiation prediction. These models were generated by varying the number of inputs for each model with the output being solar radiation. Data set of 30 years were collected from the National Space Research Development Agency (NASDRA) and procured for the presented simulation study. Simulation using ANFIS methodology was carried out using MATLAB Tool. The obtained data was divided into two categories: training and testing with training having 70% and testing 30% of the data sets. The simulation results were checked against the data and confirmed to be within allowable limits. The coefficients of determination (R2), correlation coefficient(R), Mean Square Error (MSE), Root Mean Square Error (RMSE) were calculated to demonstrate the effectiveness of the proposed machine learning models. It can be safely concluded that model 4 gave an accurate result with high efficiency and less error.
Authors and Affiliations
Asia'u T. Belgore , Ruth A. Onyohi , Najashi B. Gafai , Michael Solomon Ighodalo ,
Keywords
Related Articles
- EP ID EP719201
- DOI 10.47191/etj/v8i7.08
- Views 79
- Downloads 0
AI Chatbots in LMS: A Pedagogical Review of Cognitive, Constructivist, and Adaptive Principles
The sudden growth of technology has profoundly shifted various sectors, notably education, where Artificial Intelligence (AI) chatbots are revolutionizing Learning Management Systems (LMS). LMSs are pivotal in the manage...
INVESTIGATION OF MODEL TRANSFORMER INSULATION BEHAVIOR DURING PD ACTIVITY IN DI-BENZO-DI-SULFIDE SULPHUR CONTAMINATED TRANSFORMER OIL USING ONLINE TAN DELTA MEASUREMENT
Sulphur can be present in mineral insulating oil and can manifest in stable, highly reactive and corrosive form. The corrosive sulphur reacts with the copper conductor in transformer and forms semi conductive copper sulp...
A STUDY OF THE RELATIONSHIP BETWEEN ENVIRONMENTAL SANITATION AND EFFECTIVE LEADERSHIP
The annual report issued by the City of Tshwane for the financial year 2016/2017 shows that overall efficiency in the management of municipal solid waste generated by businesses operating in the various parts of Tshwane...
Exploring the Effectiveness of Meme-Based Learning on Nigerian University Students’ Engagement, Motivation, and Understanding of Complex Concepts: A Survey Study
This study investigated the effectiveness of meme-based learning on Nigerian university students' engagement, motivation, and understanding of complex concepts. Using a survey design, the research involved 60 students fr...
Fixed Voters Clustering to Determine the Level of Beginner Voters using Data Mining Techniques
Data mining clustering technique is used to classify the level of beginner voters using the K-Means method. Fixed voter clusters are used for decision making for stakeholders regarding the information on beginner voters...