Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Subject: search.filters.subject.Performance measurement

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    Analysis and Prediction of Fantasy Cricket Contest Winners Using Machine Learning Techniques
    (Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Karthik, K.; S. Krishnan, G.S.; Shetty, S.; Bankapur, S.; Kolkar, R.; Ashwin, T.S.; Vanahalli, M.K.
    Cricket is one of the well-known sports across the world. The increasing interest of cricket in recent years resulted in different forms like T20, T10 from test and one day format. The craze of all these formats of cricket matches today has come into online fantasy cricket league games. Dream11 is one such app that is most popular in this context, along with many similar apps. Creating a dream team of 11 players from playing 11 of both teams involves skills, ideas and luck. Predicting a winner among all the joined contestants based on the previous historical data is a challenging task. In this paper, we used a feed-forward deep neural network (DNN) classifier for predicting the winning contestant for the top three positions in a fantasy league cricket contest. The performance of the DNN approach was compared against that of state-of-the-art machine learning approaches like k-nearest neighbours (KNN), logistic regression (LR), Naive Bayes (NB), random forest (RF), support vector machines (SVM) and in predicting the fantasy cricket contest winners. Among the methods used, DNN showed the best results for all three positions, showing its consistency in predicting the winners and outperforms the state-of-the-art machine learning classifiers by 13%, 8% and 9%, respectively, for first, second and third winning positions, respectively. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Tamilnadu Omnibus Travels Evaluation Using TOPSIS and Fuzzy TOPSIS Methods
    (Springer Science and Business Media Deutschland GmbH, 2022) Vadivel, S.M.; Sequeira, A.H.; Jauhar, S.K.; Chandana, V.
    This research uses an effective fuzzy multi-criteria method to evaluate the performance of eight omnibus operators in Tamilnadu, India’s southernmost state (MA). The data was gathered from passengers (regular travelers) and the management of omnibus travel operators. Passengers provided qualitative data, while management offered quantitative data. To estimate the omnibus travels effectiveness, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique and Fuzzy TOPSIS were employed to analyze the subjective assessments of both quantitative and qualitative data. Using linguistic concepts, the subjectiveness and inaccuracy of the performance assessment methods are expressed as fuzzy numbers. Traditionally, fuzzy MA models are often used to find the degree of possibility of an alternative of each attribute and sub-attributes to avoid complicated and inaccurate comparisons of fuzzy numbers. Then, grounded on the fuzzy techniques, it is converted into a weighted fuzzy performance index for each alternative. This technique is computationally efficient, and the principles behind it are basic and straightforward to comprehend. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Application of WASPAS Method for the Evaluation of Tamil Nadu Private Travels
    (Springer Science and Business Media Deutschland GmbH, 2023) Vadivel, S.M.; Sequeira, A.H.; Shetty, D.S.; Chandana, V.
    The most important and discussion topic is providing a sustainable service to customer in satisfaction on transportation facilities. Tamil NÄ du government has taken much initiatives to introduce more buses, trains in order to satisfy the customers while travelling. Tamil NÄ du (TN) has a huge population and people are expecting more facilities from TN government. Hence, in addition, Private bus travels came into that place to provide customers has better service. This paper aims to assess the performance of eight private bus travels passengers transport company in Tamil Nadu, Chennai. The performance data have been collected from both managers and frequent travelling passengers. The quantitative data collected from travels managers whereas qualitative data collected from passengers. These quantitative and qualitative have been analyzed with WASPAS a MCDM techniques. A novel MCDM technique known as WASPAS (Weighted Aggregated Sum Product Assessment) proposed in this study. The overall systematic algorithm for determining the best private bus travels company has been illustrated in step-by-step basis for further enhancement. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.