Mahalakshmi P

Department of Instrumentation

School of Electrical Engineering

Vellore Campus

Venkatasubramanian V.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Aquaculture International

In this paper, a predictive mathematical model is proposed to identify the best alternatives from the given set of alternatives characterized by multiple criteria. An objective function is developed to find the ranking index of the alternatives. A new Comprehensive-Technique for Order Preference by Similarity to Ideal Solution (C-TOPSIS) method is proposed which combines the comprehensive weights of the criteria with TOPSIS method. The proposed predictive mathematical model generates a ranking of the alternatives. An experimental study has been carried out by taking agricultural data set of rice paddy crop to demonstrate and validate the developed model. The results show significant correlation between the ranks obtained by the proposed model and the ranks obtained from the average yield per hectare. Also the results of the proposed method outperform the results of the other ranking methods, namely VIKOR and ELECTRE, particularly in the real world example. Thus, the developed predictive mathematical model seems to provide better results for the given alternatives and can also be used for other decision-making problems. © 2018, The Natural Computing Applications Forum.

Neural Computing and Applications

Predictive mathematical model for solving multi-criteria decision-making problems

A hybrid soft decision model has been developed in this paper to take decision on agriculture crop that can be cultivated in a given experimental land by integrating few soft computing techniques. The proposed model comprises of three parts, namely weight calculation, classification and prediction. Twenty-seven input criteria were categorized into seven broad criteria, namely soil (11 sub-criteria), water (2 sub-criteria), season (no sub-criterion), input (6 sub-criteria), support (2 sub-criteria), facilities (3 sub-criteria) and risk (2 sub-criteria). In the proposed model, relative weights of main criteria were calculated using Shannon’s Entropy method and relative weights of sub-criteria in each main criterion were calculated using rough set approach. As VIKOR method is effective in sorting the alternatives, it is used to determine the ranking index of main criteria in this study. A soft decision system was constructed from the results of rough set method, VIKOR method and Shannon’s Entropy method. Classification rules were generated for five agriculture crops, namely paddy, groundnut, sugarcane, cumbu and ragi based on the soft decision system using bijective soft set approach. The developed model predicts each site in the validation dataset into one of the five crops. The performance of the proposed model has been sanity checked by agriculture experts. © 2016, The Natural Computing Applications Forum.

Multi-class classification using hybrid soft decision model for agriculture crop selection

Agriculture crop selection cannot be formulated from one criterion but from multiple criteria. A list of criteria for crop selection was identified through literature survey and agricultural experts. The identified criteria were grouped into seven main criteria namely, soil, water, season, input, support, facilities and threats. In this paper, Mahalanobis Taguchi system based tool was developed for identification of useful set of criteria which is a subset of the original criteria, for taking decision on crop selection in a given agriculture land. The combination of Mahalanobis distance and Taguchi method is used for identification of important criteria. Matlab software was used to develop the tool. After entering the values for each main criteria in the tool, it will process the value and identify the useful sub-criteria under each main criteria for selecting the suitable crop in a given agriculture land. Instead of considering all criteria, one can use these useful set of criteria under each main criteria for taking decision on crop selection in agriculture. © 2016, Indian Academy of Sciences.

Fulltext

Sādhanā

Mahalanobis Taguchi system based criteria selection tool for agriculture crops

DMTIOLA: decision making tool for identification of optimal location for aquaculture farming development

Aquaculture development suitable location is not formulated from one criterion but from multiple criteria. A list of criteria was selected by reviewing the literature and consultation with aquaculture experts and then classified into five categories namely; water, soil, support, infrastructure and risk factor. Using these criteria a Mahalanobis Taguchi System (MTS) based tool was developed to facilitate the selection of prime set of criteria, which is a subset of the original criteria for suitable aquaculture site identification. Mahalanobis Distance (MD) was used for constructing a measurement scale for the aquaculture system. The principles of Taguchi method was used for screening the important criteria in the system. The information required to make an assessment was entered into the computer program. The computer program then processes the information and produces the prime set of criteria for each category. The software program is a valuable tool for the identification of prime set of criteria within each category. One can use these prime set of criteria within each category instead of all criteria for the identification of optimal location in shrimp aquaculture.

Computers and Electronics in Agriculture

Mahalanobis Taguchi System based criteria selection for shrimp aquaculture development

Biosciences Biotechnology Research Asia

Enhancement of Antibiotic Production in Marine Bacteria

Technological and Economic Development of Economy

NEW INTERNAL RATING APPROACH FOR CREDIT RISK ASSESSMENT / NAUJAS VIDAUS REITINGU MODELIS KREDITO RIZIKOS VERTINIMUI

International Journal of Services Operations and Informatics

Selection by TOPSIS for surveyor of candidates in organisations

Journal	Data powered by TypesetAquaculture International
Publisher	Data powered by TypesetSpringer Science and Business Media LLC
ISSN	0967-6120
Open Access	0