In the field of prediction Assessment plays a major role. The prediction result becomes incorrect if a Assessment is not selected properly and the scope of future work becomes lost or unpredictable. Therefore an appropriate technique needs to be selected for the purpose of forecasting. There are lot of soft computing models which are being used in various application for the purpose of forecasting. The performance of fuzzy logic and Artificial Neural Network, in the field of soft computing, are being examined for the purpose of Assessment on the basis of average error. Here an effort is being used to select the proper soft computing technique to predict the futuristic information of quantity of exported tea to be exported in near future. Initially, the concept of Fuzzy Logic based on Fuzzy Membership Function has been applied and therefore after concept of Feed Forward Back propagation Neural Network of soft computing has been used to optimize the error.

Fuzzy Logic, Artificial Neural Network, Feed Forward Back Propagation Neural Network, Soft Computing

[1] International Journal of Applied Evolutionary Computation (IJAEC), Vol. 8 No. 3 pp. 13-52, 2017 ACM Index.
[2] G . Purkait and D.P Singh, “An effort to optimize the error using statistical and soft computing methodologies" , Journal of Applied Computer Science & Artificial Intelligence Vol .1 No. 1, pp. 15-20, 2017.
31] D.P Singh, “ A Modified Bio Inspired BAT algorithm," International Journal of Applied Metaheuristic Computing (IJAMC), Vol. 9 No. 1,pp. 60-77, 2018. Scopus Index
[4] D. P., J. P. Choudhury and M. De, “An Enhance DE algorithm for analysis in data set”, International Journal of Data Science (IJDS), 2016 (Accepted).
[5] Dharmpal Singh, Abhishek Banerjee, Gopal Purkait , “Assessment of Heart DiseaseTypes Using Clustering Techniques Under the Domain of Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol.6 Issue 03 pp. 10-16, Print ISSN: 2231-2021 e-ISSN: 2231-0312 .
[6] D. P. Singh, S. Sahana, SK Saddam Ahmed , "A Comparative Study to Assess the Crohn’s Diseasetype using Statistical and Fuzzy Logic Methodology", International Journal of Computer Sciences and Engineering, Volume-04, Issue-06, Page No (41-46), Aug -2016, E-ISSN: 2347-2693
[7] D. P. Singh, J. P. Choudhury and M. De, “An effort to select a preferable meta heuristic model for knowledge discovery in Data mining”, International Journal of mataheuristics, Vol. 4 No. 1, pp.57-90, September, 2015. 1755-2184, ISSN print: 1755-2176 DBLP Index
[8] Sk. Saddam and D. P.Singh, “Genotype based classification of Crohn’s disease using various BPN training algorithms”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 5 No. 2, pp.22-29, July, 2015, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[9] D. P. Singh, J. P. Choudhury and M. De, “A modified ACO for classification on different data set” International Journal of Computer Application, Vol.123, No. 6, pp-39-52, August 2015, ISSN 0975-8887..
[10] D. P. Singh, J. P. Choudhury and M. De, “An Effort to Compare the Clustering Technique on Different Data Set Based On Distance Measure Function in the Domain of Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 5, No. 1, pp. 1-8,January, 2015, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[11] D. P. Singh, J. P. Choudhury and M. De, “A Comparative Study to Select a Soft Computing Model for Developing the Knowledge Base of Data mining with Association Rule Formation by Factor Analysis”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 3, No. 3, pp.18-23, October, 2013, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[12] D. P. Singh, J. P. Choudhury and M. De, “An Effort to Developing the Knowledge Base in Data Mining by Factor Analysis and Soft Computing Methodology”, International Journal of Scientific & Engineering Research (IJSER), Vol. 4, No. 9, pp. 1912-1923, September, 2013, ISSN 2229-5518.
[13] D. P. Singh, J. P. Choudhury and M. De, “A comparative study on the performance of Fuzzy Logic, Bayesian Logic and neural network towards Decision Making” International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 4, No. 2, pp. 205-216, April, 2012. SSN online: 1755-8069
ISSN print: 1755-8050, Scopus Index
[14] D. P. Singh, J. P. Choudhury and M. De, “A Comparative Study to Select a Soft Computing Model for Knowledge Discovery in Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 2, No. 2, pp. 6-19, April, 2012.
[15] D. P. Singh, J. P. Choudhury and M. De, “ A Comparative Study on the performance of Soft Computing models in the domain of Data Mining,” International Journal of Advancements in Computer Science and Information Technology, Vol. 1, No. 1, pp. 35-49, September, 2011, ISSN 2277-9140.
[16] D. P. Singh, J. P. Choudhury and M. De, “Optimization of fruit quantity by different types of cluster technique”, Journal of Computer Sciences, Punjab, Vol. 9, No.1, pp. 17-28, June-July, 2011, ISSN 0973-4058.
[17] D. P. Singh, J. P. Choudhury and M. De, “Performance measurement of Soft Computing models based on
Residual Analysis”, International Journal for Applied Engineering and Research, Vol. 6, No. 5, Delhi, India, pp. 823-832, Jan-July, 2011, Print ISSN 0973-4562. Online ISSN 1087-1090. Scopus Index
[18] D. P. Singh, J. P. Choudhury and M. De, “Optimization of Fruit Quantity by comparison between Statistical Model and Fuzzy Logic by Bayesian Net work”, PCTE, Journal of Computer Sciences, Vol. 8, No.1, Punjab, pp. 91-95, June-July, 2010.
[19] D. P. Singh, J. P. Choudhury and M. De, “Prediction Based on Statistical and Fuzzy Logic Membership Function”, PCTE, Journal of Computer Sciences, Vol. 8, No. 1, Punjab, pp. 86-90 , June-July, 2010.
[20] D.P. Singh, J. P. Choudhury and M. De, “Performance Measurement of Neural Net work Model Considering Various Membership Functions under Fuzzy Logic”, International Journal of Computer and Engineering, Vol. 1, No. 2, pp. 1-5, 2010, ISSN-0976-9587.
[21] D. P. Singh, J. P. Choudhury, “Assessment of Exported Mango Quantity by Soft Computing Model”, International Journal of Information Technology and Knowledge Management, Kurukshetra University, Vol. 2, No. 2, pp. 393-395, June-July, 2009, ISSN : 0973-4414 .