Fish Production Forecasting in India using Nested Interval Based Fuzzy Time Series Model
Amit Kumar Rana
Amit Kumar Rana, Assistant Professor in Department of Mathematics, Swami Vivekanand Subharti University, Meerut, Uttar Pradesh, India.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5534-5537 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9412038620/2020©BEIESP | DOI: 10.35940/ijrte.F9412.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The livestock and agriculture is like lifeline of Indian villagers and economy. India is ranked first in livestock population and second in fish production. Fish is major part of eating in south and most of eastern part of India and use aquaculture for fish production India s also a major producer of fish through aquaculture, and ranks second in the world. In such condition forecasting of livestock is important in making policies and marketing, planning of products related to livestock and fishes. Fuzzy time series (FTS) is of great importance for such forecasting. But the problem with FTS forecast lies with the accuracy. There are many methods for linguistic values as variables for data of time series, but limitations starts with the error in forecasted and actual value. The present work studies the forecasting of fish production in India rainfall forecasting by FTS using two interval differences is proposed. The presented method is tested on the official data of deptt. of Animal Husbandry, Dairying and Fisheries, Government of India and compared with Chen’s models used for university enrollment. The forecasted values shows better result compared to Chen model.
Keywords: Fish production, Fuzzy time series (FTS), Fuzzy logical relations (FLR), Nested difference interval.
Scope of the Article: Production.