Decision-making method based on rough set and evidential theory for greenhouse environmental control

Aiming at the requirements of expert decision-making for greenhouse environmental control, an inference method based on rough set and evidential theory was proposed. The decision-making model includes continuous variables discretization, formation of expert decision-making table, attribute reduction and evidence combination. The decision-making model was established by four steps. Firstly, discrete the consecutive environment index data through fuzzy C means clustering method. Secondly, optimize decision table by using attribute reduction algorithm based on information entropy, so that to eliminate the redundancies of expert knowledge. Thirdly, introduce the theory of evidence to process the optimized index. Finally, judge an appropriate greenhouse control method according to basic probability distribution decision. The case study indicates that decision making method can greatly enhance the reliability of decision-making and reduce its inference uncertainty, which has an important significance to the application in greenhouse environmental control.