Open AccessIntelligent model for reservoir operation through data mining-A Case study
Author(s) -
V. Gopinath,
S. Mohan,
G. Kangadharan,
Ang Chun Kit,
Prasanna Amur Varadarajan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2040/1/012032
Subject(s) - fuzzy logic , heuristic , computer science , context (archaeology) , knowledge acquisition , operator (biology) , artificial intelligence , data mining , industrial engineering , engineering , paleontology , biochemistry , chemistry , repressor , transcription factor , gene , biology
Classical discrete mathematics could not model complex and uncertain systems effectively. These discrete mathematical equations can be replaced by a method of fuzzy logic systems wherein the operational laws are expressed in linguistic terms. Fuzzy logic means it is the form of knowledge acquisition to be suitable for notions that cannot be defined as precisely as discrete mathematics would do. But it depends upon their context, knowledge acquisition to enable the computerized devices to think like humans. The Matlab was employed to develop the operation model of the Vaigai reservoir which is in South India. Fuzzy logic control was successfully found to be a logical way for mapping between input and output variables of the operation of a reservoir. The objective of the study was to capture the experience gained over past years of operation of the Vaigai system so that the experiential knowledge was made available to the operator for assisting him inefficient management of the reservoir. The data mining helped to develop an improved database for heuristic models such as the non-crisp model for deriving an effective monthly operational policy for Vaigai reservoir.