A hybrid approach using AHP–TOPSIS methods for ranking of soft computing techniques based on their attributes for prediction of solar radiation

• DOI: 10.1016/j.envc.2022.100634
• Publication Date: 2022-10-12T11:57:45Z
• Authors: Shadab Ahmad; Mohd Parvez; Tasmeem Ahmad Khan; Osama Khan
• Keywords: TOPSIS; Ideal solution; Soft Computing

Recent developments in solar equipment's have motivated researchers to formulate an accurate measurement system for radiation under varying environment circumstances that could prove be economical and viable. To furnish precise estimators of radiation, multiple models different background are employed which capable solving complex non-linear data collection processing problems. These immensely proficient predicting by means numerous algorithms functions. Current research compares the prediction capability several on various criteria's such as accuracy, cost, time skill requirement. The present study is accomplished New Delhi, India using hybrid combination two Multi Criteria Estimators methods. Weights were calculated Analytical Hierarchical Process assigned each performance attribute. Accuracy most significant attribute its percentage contribution maximum (48.28%) followed requirement (31.38%), (14.41%), cost (5.9%). Furthermore, then ranks these basis their attributes with aid Technique Order Preference Similarity Ideal Solution. Among all models, Artificial Neural Network model was ranked best application field energy, very closely Support Vector Machine while Response Surface Methodology came out least favourite.