Junde Chen¹, Jiajia Yuan², Weirong Chen³, Adnan Zeb⁴, Md Suzauddola⁵, Yaser A. Nanehkaran^2,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2575-2591, 2024, DOI:10.32604/cmc.2024.048522 - 27 February 2024

Abstract Missing value is one of the main factors that cause dirty data. Without high-quality data, there will be no reliable analysis results and precise decision-making. Therefore, the data warehouse needs to integrate high-quality data consistently. In the power system, the electricity consumption data of some large users cannot be normally collected resulting in missing data, which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate. For the problem of missing electricity consumption data, this study proposes a group method of data handling (GMDH) based… More >

Ishak Hashim¹, Nur Nabilah Che Draman², Samsul Ariffin Abdul Karim^3,*, Wee Ping Yeo⁴, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 221-236, 2021, DOI:10.32604/cmc.2021.016006 - 04 June 2021

Abstract This paper discusses scattered data interpolation using cubic trigonometric Bézier triangular patches with continuity everywhere. We derive the condition on each adjacent triangle. On each triangular patch, we employ convex combination method between three local schemes. The final interpolant with the rational corrected scheme is suitable for regular and irregular scattered data sets. We tested the proposed scheme with 36,65, and 100 data points for some well-known test functions. The scheme is also applied to interpolate the data for the electric potential. We compared the performance between our proposed method and existing scattered data interpolation More >