Gu, L. (2016) A Novel Subtractive Clustering by Using K-Harmonic Means Clustering for Initialization. 7th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, 26-28 August 2016, 840-843.
https://doi.org/10.1109/ICSESS.2016.7883197

has been cited by the following article:

• TITLE: Data Prediction Model Using Combination of Clustering and Fuzzy Technique

  AUTHORS: Md. Mafiul Hasan Matin, Tanzim Kabir, Amina Khatun, Md. Imdadul Islam

  KEYWORDS: Subtractive Clustering, Fuzzy Interface System, ANN, Scatterplot and Surface Plot

  JOURNAL NAME: Journal of Computer and Communications, Vol.8 No.7, July 30, 2020

  ABSTRACT: The analysis of environmental daily evaporation plays a vital role in the field of agriculture. It is very essential to know the daily evaporation rate of a particular area for proper cultivation. So, we need a standard prediction model which can predict the daily evaporation. In this paper, we use subtractive clustering and Fuzzy logic to predict daily evaporation of a particular area. The input data used in the paper are: maximum soil temperature, average soil temperature, average air temperature, minimum relative humidity, average relative humidity and total wind, which are related to the daily evaporation of a particular area as the output. The accuracy of output of the paper is compared with the previous model of Artificial Neural Network (ANN) and we get better result towards the target value. The finding of the paper is applicable in environmental science, geological science and agriculture.