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Dr.Phayung Meesad
Dr.Phayung Meesad
Associate Professor, Department of Information Technology Management & Director of Central Library 0-2555-2708, 2711
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Education 
1994 Bachelor of Science in Technical Education (Teacher Training in Electrical Engineering), King Mongkut’s University of Technology North Bangkok.
1998 Master of Science (Electrical and Computer Engineering), Oklahoma State University, Stillwater, USA.
2002 Doctoral of Philosophy (Electrical and Computer Engineering), Oklahoma State University, Stillwater, USA.

Research of Interest
Computational Intelligence, Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, Data Science, Data Mining, Digital Signal Processing, Image Processing, Business Intelligence, Time Serires Analysis, Natural Language Processing.

Selected Publications

Bo, M. M., Meesad, P. (2018), Mining Patterns in Housing Characteristics of Migrants, 18th International Symposium on Communications and Information Technologies (ISCIT 2018), Sukosol Hotel, Bangkok, Thailand, 26-28 September 2018.

Rasel, R.I., Sultana, N., Akhter, S., Meesad, P. (2018), Detection of Cyber-Aggressive Comments on Social Media Networks: A Machine Learning and Text mining approach, 2nd International Conference on Natural Language Processing and Information Retrieval (NLPIR 2018), Riverineplace, Nonthaburi, Thailand, 7-9 September 2018.

Suksakaophong, P., Meesad, P., Unger, H. (2018), ARMFEG: Association rule mining by frequency-edge-graph for rare items, 14th International Conference on Computing and Information Technology (IC2IT 2018), Shangri-La Hotel, Chiang Mai, Thailand, 5-6 July 2018.

Jitsakul, W., Meesad, P., Sodsee, S. (2018), Enhancing comment Feedback classification using text classifiers with word centrality measures, Proceeding of 2nd International Conference on Information Technology (INCIT 2017), pp. 1-5.

Rasel, R.I., Sultana, N., Meesad, P. (2018), An application of data mining and machine learning for weather forecasting, Advances in Intelligent Systems and Computing, 566, pp. 169-178.

Kubek, M. M., Meesad, P., Unger, H., (2017), “User-based document ranking,” ACM International Conference Proceeding Series, Part F133874, pp. 119-123.

Tapsai, C., Meesad, P., Haruechaiyasak, C. (2017) “Natural language semantic model for arithmetic sentences,” ACM International Conference Proceeding Series, Part F133874, pp. 175-179.

Boonyopakorn, P., Meesad, P. (2017) “The evaluated measurement of a combined genetic algorithm and artificial immune system,” International Journal of Electrical and Computer Engineering, 7(4), pp. 2071-2084.

Boonyopakorn, P., Meesad, P. (2017) “A hybrid immune genetic algorithm to solve university time table problems,” Walailak Journal of Science and Technology, 14(10Special Issue), pp. 825-835.

Boonyopakorn, P., Meesad, P. (2017) “The performance evaluation of a hybrid immune genetic algorithm based on mathematical functions,” 20th International Computer Science and Engineering Conference: Smart Ubiquitos Computing and Knowledge, ICSEC 2016, art. no. 7859880.

Kadmateekarun, P., Meesad, P., Nuanmeesri, S. (2017) “Comparing techniques for sentiment analysis in cosmetic industry from Thai reviews videos,” Journal of Engineering and Applied Sciences, 12 (2), pp. 397-403.

Mahmud, M.S., Meesad, P. An innovative recurrent error-based neuro-fuzzy system with momentum for stock price prediction (2016) Soft Computing, 20 (10), pp. 4173-4191.

Li, J., Meesad, P. Combining Sentiment Analysis with Socialization Bias in Social Networks for Stock Market Trend Prediction (2016) International Journal of Computational Intelligence and Applications, 15 (1), art. no. 1650003.

Van Hieu, D., Meesad, P. A cell-MST-based method for big dataset clustering on limited memory computers (2016) Proceedings – 2015 7th International Conference on Information Technology and Electrical Engineering: Envisioning the Trend of Computer, Information and Engineering, ICITEE 2015, art. no. 7409023, pp. 632-637.

van Hieu, D., Meesad, P. A fast outlier detection algorithm for big datasets (2016) Advances in Intelligent Systems and Computing, 463, pp. 159-169.

van Hieu, D., Meesad, P. Cell-DROS: A fast outlier detection method for big datasets (2016) International Journal of Advances in Soft Computing and its Applications, 8 (3), pp. 1-17. ·

Long, N.C., Meesad, P., Unger, H., A highly accurate firefly based algorithm for heart disease prediction, (2015) Expert Systems with Applications, 42 (21), art. no. 10101, pp. 8221-8231.

Mahmud, M.S., Meesad, P. An innovative recurrent error-based neuro-fuzzy system with momentum for stock price prediction, (2015) Soft Computing, 19 p. Article in Press.

Hieu, D.V., Meesad, P. Fast K-Means clustering for very large datasets based on mapreduce combined with a new cutting method, (2015) Advances in Intelligent Systems and Computing, 326, pp. 287-298.

Long, N.C., Wisitpongphan, N., Meesad, P., Unger, H., Clustering stock data for multi-objective portfolio optimization, (2014) International Journal of Computational Intelligence and Applications, 13 (2), art. no. 1450011, .

Van Hieu, D., Smanchat, S., Meesad, P., MapReduce join strategies for key-value storage, (2014) 11th Int. Joint Conf. on Computer Science and Software Engineering: “Human Factors in Computer Science and Software Engineering” – e-Science and High Performance Computing: eHPC, JCSSE 2014, art. no. 6841861, pp. 164-169.

Thammasiri, D., Delen, D., Meesad, P., Kasap, N., A critical assessment of imbalanced class distribution problem: The case of predicting freshmen student attrition, (2014) Expert Systems with Applications, 41 (2), pp. 321-330.

Van Hieu, D., Wisitpongphan, N., Meesad, P., Analysis of factors which impact Facebook users’ attitudes and behaviours using decision tree techniques, (2014) 2014 11th Int. Joint Conf. on Computer Science and Software Engineering: “Human Factors in Computer Science and Software Engineering” – e-Science and High Performance Computing: eHPC, JCSSE 2014, art. no. 6841880, pp. 274-279.

Meesad, P.. An interval type-2 fuzzy system with hybrid intelligent learning, (2014) 4th World Congress on Information and Communication Technologies, WICT 2014, art. no. 7077276, pp. 263-268.

Long, N.C., Meesad, P., An optimal design for type-2 fuzzy logic system using hybrid of chaos firefly algorithm and genetic algorithm and its application to sea level prediction, (2014) Journal of Intelligent and Fuzzy Systems, 27 (3), pp. 1335-1346.

Meesad, P., Li, J., Stock trend prediction relying on text mining and sentiment analysis with tweets (2014) 2014 4th World Congress on Information and Communication Technologies, WICT 2014, art. no. 7077275, pp. 257-262.

Boonkrong, S., Unger, H., Meesad, P. Recent Advances in Information and Communication Technology: Proceedings of the 10th International Conference on Computing and Information Technology (IC2IT2014) (2014) Advances in Intelligent Systems and Computing, 265 AISC, .

Long, N.C., Meesad, P., Unger, H. Attribute Reduction Based on Rough Sets and the Discrete Firefly Algorithm (2014) Advances in Intelligent Systems and Computing, 265 AISC, pp. 13-22.

Mahmud, M.S., Meesad, P. Time series stock price prediction using recurrent error based neuro-fuzzy system with momentum (2014) 2014 International Electrical Engineering Congress, iEECON 2014, art. no. 6925866, .

Thanh, H.T.P., Meesad, P. Stock market trend prediction based on text mining of corporateweb and time series data (2014) Journal of Advanced Computational Intelligence and Intelligent Informatics, 18 (1), pp. 22-31.

Buathong, W., Meesad, P. Double linear support vector machine for dimensionality reduction (2014) Research Journal of Applied Sciences, 9 (4), pp. 208-213.

Long, N.C., Meesad, P. Meta-heuristic algorithms applied to the optimization of type-1 and type 2 TSK fuzzy logic systems for sea water level prediction (2013) 2013 IEEE 6th International Workshop on Computational Intelligence and Applications, IWCIA 2013 – Proceedings, art. no. 6624787, pp. 69-74.

Meesad, P., Rasel, R.I. Predicting stock market price using support vector regression (2013) 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013, art. no. 6572570, .

Meesad, P., Rasel, R.I. Dhaka stock exchange trend analysis using support vector regression (2013) Advances in Intelligent Systems and Computing, 209 AISC, pp. 135-143.

Buathong, W., Meesad, P. Enhancing the efficiency of dimensionality reduction using a combined linear SVM weight with relieff feature selection method (2013) Advances in Intelligent Systems and Computing, 209 AISC, pp. 125-134.