AGRICULTURE CROP SIMULATION MODELS USING COMPUTATIONAL INTELLIGENCE
Journal Title: International Journal of Computer Engineering & Technology (IJCET) - Year 2019, Vol 10, Issue 3
Abstract
Variation in the climatic conditions is the major hurdle in the Agriculture sector to attain high crop yield. The Crop simulation models portray the stage-wise growth of crop with the respective environment condition. The crop simulation models help the farmer to make better decisions for improving the crop yield. Artificial Intelligence, Data mining and Computational Intelligent are becoming more prominent in the agriculture field for decision making because of emerging technology such as GIS, Satellite data and remote sensing data in agriculture. This paper reviews information on crop simulation models using computational intelligence and their application. It also reviews the different types of crop simulation models and their limitation in Agriculture. It also discusses the different crop simulation models in details. Considering the emerging technology in the agriculture field we discussed the future trends of crop simulation models.
Authors and Affiliations
P. K. KOSAMKAR, V. Y. KULKARNI
Keywords
Related Articles
- EP ID EP46567
- DOI 10.34218/IJCET.10.3.2019.015
- Views 218
- Downloads 0
STOCK MARKET PREDICTION USING MACHINE LEARNING METHODS
Stock price forecasting is a popular and important topic in financial and academic studies. Share market is an volatile place for predicting since there are no significant rules to estimate or predict the price of a sh...
MACHINE AS ONE PLAYER IN INDIAN COWRY BOARD GAME: ADVANCED PLAYING STRATEGIES
Cowry game, also known as Chowka Bhara, is an ancient board game originated in India. It is a 2-4 player strategic race game which contains an element of chance due to the throw of special dice (cowry shells). This gam...
DIABETES CLASSIFICATION AND PREDICTION USING ARTIFICIAL NEURAL NETWORK
The classification of data is an important field of data mining comes under supervised learning. In this approach classifier is trained on the pre-categorized data thereafter tested on unseen part called test data to e...
ENHANCED CLUSTER HEAD MANAGEMENT IN LARGE SCALE WIRELESS SENSOR NETWORK USING PARTICLE SWARM OPTIMIZATION (PSO) ON THE BASIS OF DISTANCE, DENSITY & ENERGY
Wireless Sensor Networks (WSNs) are utilized for a plethora of applications such as weather forecasting, monitoring systems, surveillance, and so on. The critical issues of the WSN are energy constraints, limited memor...
DISTRIBUTED CONTROLLER FAULT TOLERANCE MODEL (DCFT) USING LOAD BALANCING IN SOFTWARE DEFINED NETWORKING
Lack of Flexibility, Centralized Control, and Cost are limitations of the traditional network. Software defined networking (SDN) adds flexibility and programmability in network management by separating the control plan...