An Expert System for Control of Anaerobic Digesters

1992 ◽  
Author(s):  
P. Pullammanappallil ◽  
S.A. Svoronos ◽  
G. Lyberatos ◽  
D.P. Chynoweth
Keyword(s):  
Expert System ◽  
Anaerobic Digesters

Expert system for control of anaerobic digesters

1998 ◽  
Vol 58 (1) ◽  
pp. 13-22 ◽  
Author(s):  
P. C. Pullammanappallil ◽  
S. A. Svoronos ◽  
D. P. Chynoweth ◽  
G. Lyberatos
Keyword(s):  
Expert System ◽  
Anaerobic Digesters

Advanced monitoring and control of anaerobic wastewater treatment plants: diagnosis and supervision by a fuzzy-based expert system

2001 ◽  
Vol 43 (7) ◽  
pp. 191-198 ◽  
Author(s):  
A. Puñal ◽  
J. Rodríguez ◽  
A. Franco ◽  
E. F. Carrasco ◽  
E. Roca ◽  
...  
Keyword(s):  
Expert System ◽  
Expert Knowledge ◽  
Wastewater Treatment Plants ◽  
Rule Base ◽  
Monitoring And Control ◽  
Anaerobic Digesters ◽  
On Line ◽  
And Control ◽  
Logic Inference ◽  
Microsoft Windows

A fuzzy-based expert system (ES) for the diagnosis and supervision for anaerobic digesters is presented. The system was developed in a Microsoft Windows support using fuzzy logic inference together with a rule base for the implementation of expert knowledge. The ES runs on-line through three main modules, which determine the state and trend of the process, and the best set points for the actuation on the final control elements of the plant. Two further modules run in parallel, when they are required by the operator, using off-line and on-line information for the detection of inhibition due to toxic compounds in the process and for the validation of the on-line diagnosis. The diagnosis and supervision ES was tuned up in order to adjust the membership functions describing the process, and lately tested, running on-line, to study the response of the rule base.

An expert system for FMS control

1993 ◽  
Vol 2 (4) ◽  
pp. 223 ◽  
Author(s):  
Wang Chengen ◽  
Zhu Jianying ◽  
Wei Zhongxin
Keyword(s):  
Expert System

HAZARD: An Expert System for Risk Assessment of Environmental Chemicals

1987 ◽  
Vol 26 (01) ◽  
pp. 13-23 ◽  
Author(s):  
H. W. Gottinger
Keyword(s):  
Expert System ◽  
Structural Information ◽  
Chemical Carcinogenesis ◽  
Structural Features ◽  
Environmental Chemicals ◽  
Chemical Carcinogens ◽  
Carcinogenic Activity ◽  
Current State ◽  
Structure Activity ◽  
Carcinogenic Potential

AbstractThe purpose of this paper is to report on an expert system in design that screens for potential hazards from environmental chemicals on the basis of structure-activity relationships in the study of chemical carcinogenesis, particularly with respect to analyzing the current state of known structural information about chemical carcinogens and predicting the possible carcinogenicity of untested chemicals. The structure-activity tree serves as an index of known chemical structure features associated with carcinogenic activity. The basic units of the tree are the principal recognized classes of chemical carcinogens that are subdivided into subclasses known as nodes according to specific structural features that may reflect differences in carcinogenic potential among chemicals in the class. An analysis of a computerized data base of known carcinogens (knowledge base) is proposed using the structure-activity tree in order to test the validity of the tree as a classification scheme (inference engine).

ANALYSIS OF PLANT FRAGARIA XANANASSA DISEASE DIAGNOSES USING PRODUCTION RULES BASE ON EXPERT SYSTEM

2020 ◽  
Vol 16 (1) ◽  
pp. 25-32
Author(s):  
Basiroh Basiroh ◽  
Wiji Lestari
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
General Public ◽  
Insect Pests ◽  
Fruit Rot ◽  
Proper Treatment ◽  
Harvest Time ◽  
Production Rules

Errors that occur in solving problems in strawberry plants (Fragaria Xananassa) such as the presence of leaf patches, fruit rot, perforated leaves, and insect pests can be the cause of not maximum in harvest time. The farmers and the general public who planted strawberry (Fragaria Xananassa) need to know the proper treatment of diseases and pests so that future yields as expected. Therefore, it takes an application as a solution in the delivery of information related to the problems that are often encountered in strawberry plants (Fragaria Xananassa). Methods of production rules can be used to diagnose the disease strawberry (Fragaria Xananassa) based on signs or symptoms that occur in the parts of plants and strawberry, the results of diagnosis using this method are the same as we do Consultation on experts.  The purpose of this study was to determine the early diagnosis of disease in strawberry plants (Fragaria Xananassa) based on signs or symptoms that occur in the plant and fruit parts. The results of the analysis of this study showed that the validation of disease and symptom data in strawberry plants (Fragaria Xananassa) reached 99%, meaning that between the data of symptoms and disease understudy the accuracy was guaranteed with the experts.

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