Fuzzy cognitive map based approach for predicting yield in cotton crop production as a basis for decision support system in precision agriculture application

نویسندگان

  • Elpiniki I. Papageorgiou
  • Athanasios T. Markinos
  • Theofanis A. Gemtos
چکیده

This work investigates the process of yield prediction in cotton crop production using the soft computing technique of fuzzy cognitive maps. Fuzzy cognitive map (FCM) is a fusion of fuzzy logic and cognitive map theories, and is used formodeling and representing experts’ knowledge. It is capable of dealingwith situations including uncertain descriptions using similar procedure such as human reasoning does. It is a challenging approach for decision making especially in complex processing environments. The FCM approach presented herewas chosen to be utilized in agriculture because of the nature of the application. The prediction of yield in cotton production is a complex process with sufficient interacting parameters and FCMs are suitable for this kind of problem. Throughout this proposed method, FCMs designed and developed to represent experts’ knowledge for cotton (Gossypium hirsutum L.) yield prediction and crop management. The developed FCM model consists of nodes linked by directed edges, where the nodes represent the main factors affecting cotton crop production such as texture, organic matter, pH, K, P, Mg, N, Ca, Na and cotton yield, and the directed edges show the cause–effect (weighted) relationships between the soil properties and cotton yield. The investigated methodology was evaluated for 360 cases measured during the time of six subsequent years (2001–2006) in a 5ha experimental cotton field, in predicting the yield class between two possible categories (“low” and “high”). The results obtained reveal its comparative advantage over the benchmarking machine learning algorithms tested for the same data set for the years mentioned by providing decisions that match better with the real measured ones. The main advantage of this approach is its simple structure and flexibility, representing knowledge visually and more descriptively. Hence, it might be a convenient tool in predicting cotton yield and improving crop management. © 2011 Elsevier B.V. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Soft Computing Technique of Fuzzy Cognitive Maps to connect yield defining parameters with yield in Cotton Crop Production in Central Greece as a basis for a decision support system for precision agriculture application

This work investigates the yield and yield variability prediction in cotton crop. Cotton crop management is a complex process with interacting parameters like soil, crop and weather factors. The soft computing technique of fuzzy cognitive maps (FCMs) was used for modeling and representing experts’ knowledge. FCM, as a fusion of fuzzy logic and cognitive map theories, is capable of dealing with ...

متن کامل

Exploring Precision Farming Scenarios Using Fuzzy Cognitive Maps

One of the major problems confronted in precision agriculture is uncertainty about how exactly would yield in a certain area respond to decreased application of certain nutrients. One way to deal with this type of uncertainty is the use of scenarios as a method to explore future projections from current objectives and constraints. In the absence of data, soft computing techniques can be used as...

متن کامل

Z-Cognitive Map: An Integrated Cognitive Maps and Z-Numbers Approach under Cognitive Information

Usually, in real-world engineering problems, there are different types of uncertainties about the studied variables, which can be due to the specific variables under investigation or interaction between them. Fuzzy cognitive maps, which addresses the cause-effect relation between variables, is one of the most common models for better understanding of the problems, especially when the quantitati...

متن کامل

Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms

Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...

متن کامل

A spatial decision support system for prioritizing 22 Districts of Tehran for construction of multiplex buildings

A multiplex is a kind of urban cultural facilities which not only has several different rooms for showing films, but also provides other services such as a wide range of food and drink stores and free/easy available parking. Multiplexes have significant cultural, economic and social characteristics. Given the importance and advantages of multiplexes, several multiplex buildings have been built ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Appl. Soft Comput.

دوره 11  شماره 

صفحات  -

تاریخ انتشار 2011