Intelligent Modeling for the food chain using Fuzzy Cognitive Maps
Session
Computer Science and Communication Engineering
Description
The development of a methodological framework for evaluating the quality of a “product” on a food chain is an important issue for the management of agriculture applications. This paper addresses this issue from an intelligent point of view. The main objective of this research is the systematic examination of all main processes that make up this complex process and, at the same time, the consideration of a model for the evaluation of the quality of the “product”, considering the “intelligent modelling” of the quality of all the individual stages of the agricultural process in delivering a high quality “product” to the customer. For evaluating and extracting the quality index, the intelligent control technique is used as a non-parametric method for managing the data that make up the final
decision. Intelligent Control is the result of the application of computational in- telligence in system control. It addresses the problem of Control from a distinct
perspective from the conventional control model. Knowledge and experience of experts form the core of the process and are the basis for the learning method that makes up the control model The objective of an intelligent controller is its function like the human operator, with the same rules but without its weaknesses, while avoiding non-consistency
so that there is a uniform and standardized framework for managing the parame- ters that lead to the final solution.
Prior to the formulation of the evaluation method, exactly the parameters that affect the quality of the “product” must be defined, and at the same time, they will be analyzed. The entire production process is initially divided into three (4) basic steps: 1. “Product” collection, where the “product” is collected from the farm, 2. “Product” processing, which includes all the individual steps required for the qualitative upgrading of the raw material, 3. Packaging and storing the final “product”, 4. Distribution and delivery of the “product” to final “consumers”. In this research study, the methodology of Fuzzy Cognitive Maps is used. To implement it on the generic approach just described, the farm product of milk is
used. Simulation studies are performed, and the results are presented in the pre- sented paper. Discussion of the promising results is discussed, and future research
is presented.
Keywords:
Fuzzy Cognitive Maps; Food Chain
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-50-5
Location
UBT Kampus, Lipjan
Start Date
29-10-2022 12:00 AM
End Date
30-10-2022 12:00 AM
DOI
10.33107/ubt-ic.2022.282
Recommended Citation
Athanasoula, Ifigeneia; Apostolopoulos, Ioannis D.; and Groumpos, Peter P., "Intelligent Modeling for the food chain using Fuzzy Cognitive Maps" (2022). UBT International Conference. 291.
https://knowledgecenter.ubt-uni.net/conference/2022/all-events/291
Intelligent Modeling for the food chain using Fuzzy Cognitive Maps
UBT Kampus, Lipjan
The development of a methodological framework for evaluating the quality of a “product” on a food chain is an important issue for the management of agriculture applications. This paper addresses this issue from an intelligent point of view. The main objective of this research is the systematic examination of all main processes that make up this complex process and, at the same time, the consideration of a model for the evaluation of the quality of the “product”, considering the “intelligent modelling” of the quality of all the individual stages of the agricultural process in delivering a high quality “product” to the customer. For evaluating and extracting the quality index, the intelligent control technique is used as a non-parametric method for managing the data that make up the final
decision. Intelligent Control is the result of the application of computational in- telligence in system control. It addresses the problem of Control from a distinct
perspective from the conventional control model. Knowledge and experience of experts form the core of the process and are the basis for the learning method that makes up the control model The objective of an intelligent controller is its function like the human operator, with the same rules but without its weaknesses, while avoiding non-consistency
so that there is a uniform and standardized framework for managing the parame- ters that lead to the final solution.
Prior to the formulation of the evaluation method, exactly the parameters that affect the quality of the “product” must be defined, and at the same time, they will be analyzed. The entire production process is initially divided into three (4) basic steps: 1. “Product” collection, where the “product” is collected from the farm, 2. “Product” processing, which includes all the individual steps required for the qualitative upgrading of the raw material, 3. Packaging and storing the final “product”, 4. Distribution and delivery of the “product” to final “consumers”. In this research study, the methodology of Fuzzy Cognitive Maps is used. To implement it on the generic approach just described, the farm product of milk is
used. Simulation studies are performed, and the results are presented in the pre- sented paper. Discussion of the promising results is discussed, and future research
is presented.