ระบบข้อมูลงานวิจัย วิทยาลัยการคอมพิวเตอร์

Reference (APA)

Publications (In the Last 5 Years)

[1]

BiGCAN: A novel SRS-based bidirectional graph Convolution Attention Network for dynamic user preference and next-item recommendation ( N. Kannikaklang, W. Thamviset, S. Wongthanavasu), Expert Systems with Applications, 265, 2025. [url] [doi]

[2]

Research on Hybrid Architecture Neural Networks for Time Series Prediction ( F. Zhuang, P. Horata, T. Chen, K. Sunat), IEEE Access, 2025, , 2025. [url] [doi]

[3]

LSTM-RVFL-Attention: A Novel Hybrid Deep Learning Model for Accurate Sales Prediction ( T. Chen, P. Horata, F. Zhuang, K. Sunat), 2025 5th International Conference on Advances in Electrical, Electronics and …, 2025, , 2025. [url] [doi]

[4]

Llm-Based Code Comment Summarization: Efficacy Evaluation and Challenges ( C. Soomlek), 2025 17th International Conference on Knowledge and Smart Technology Kst 2025, , 2025. [url] [doi]

[1]

Service priority classification using machine learning ( T. Boonprapapan, P. Seresangtakul, P. Horata), Science, Engineering and Health Studies, 18, 2024. [url] [doi]

[2]

Bias-Boosted ELM for Knowledge Transfer in Brain Emotional Learning for Time Series Forecasting ( S. Iamsa-At, P. Horata, K. Sunat), IEEE Access, 12, 2024. [url] [doi]

[3]

Attribute reduction with fuzzy divergence-based weighted neighborhood rough sets ( N. Thuy, S. Wongthanavasu), International Journal of Approximate Reasoning, 173, 2024. [url] [doi]

[4]

BiG: Bidirectional Graph Convolutional Networks for Social and Sequential Recommendation ( N. Kannikaklang, S. Wongthanavasu), International Computer Science and Engineering Conference, , 2024. [url] [doi]

[5]

BiHGCA: A Novel SRS-Based Bidirectional Hyperbolic Graph Capsule Co-Attention Network for User Preference Drift ( N. Kannikaklang, W. Thamviset, S. Wongthanavasu), IEEE Access, 12, 2024. [url] [doi]

[6]

BiLSTCAN: A Novel SRS-Based Bidirectional Long Short-Term Capsule Attention Network for Dynamic User Preference and Next-Item Recommendation ( N. Kannikaklang, W. Thamviset, S. Wongthanavasu), IEEE Access, 12, 2024. [url] [doi]

[7]

Early-Stage Cholangiocarcinoma Detection Using Surface-Enhanced Raman Spectroscopy and 1D CNN with Discrete Wavelet Transform ( P. Danvirutai, S. Wongthanavasu, C. Pairojkul, C. Srichan, S. Pinlaor), 2024 16th Biomedical Engineering International Conference (BMEiCON), 1-5, 2024, , 2024. [url] [doi]

[8]

MULTI-CLASS TEXT CLASSIFICATION ON KHMER NEWS ARTICLES USING DEEP LEARNING MODELS WITH OPTIMAL HYPERPARAMETERS ( C. Soomlek), Icic Express Letters, 18, 2024. [url] [doi]

[9]

An Adaptive Smell Agent Optimization with Binomial Crossover and Linnik Flight for Engineering Optimization Problems ( C. Soomlek), International Computer Science and Engineering Conference, , 2024. [url] [doi]

[10]

Automated Sequence Labeling for Causality Extraction in Medical Domain ( C. Soomlek), International Computer Science and Engineering Conference, , 2024. [url] [doi]

[1]

Deep Cellular Automata-Based Feature Extraction for Classification of the Breast Cancer Image ( S. Tangsakul, S. Wongthanavasu), Applied Sciences (Switzerland), 13, 2023. [url] [doi]

[2]

An Efficient Cellular Automata-Based Classifier with Variance Decision Table ( P. Wanna, S. Wongthanavasu), Applied Sciences (Switzerland), 13, 2023. [url] [doi]

[3]

Enhanced Machine Learning-Based Code Smell Detection Through Hyper-Parameter Optimization ( C. Soomlek), Proceedings of Jcsse 2023 20th International Joint Conference on Computer Science and Software Engineering, , 2023. [url] [doi]

[4]

Multi-Class Text Classification on Khmer News Using Ensemble Method in Machine Learning Algorithms ( R. Phann, C. Soomlek, P. Seresangtakul), Acta Informatica Pragensia, 12, 2023. [url] [doi]

[5]

Exploration of the Feasibility and Applicability of Domain Adaptation in Machine Learning-Based Code Smell Detection ( C. Soomlek), Communications in Computer and Information Science, 1942, 2023. [url] [doi]

[1]

Generalized stability of artificial emotional neural network in predicting domestic power peak demand ( S. Iamsa-At, P. Horata, K. Sunat), Science, Engineering and Health Studies, 16, 2022. [url] [doi]

[2]

Incident Task Sequence for Service Priority using Cosine Similarity ( T. Boonprapapan, P. Horata, P. Seresangtakul), Proceedings - 2022 1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022, , 2022. [url] [doi]

[3]

A Novel Feature Selection Method for High-Dimensional Mixed Decision Tables ( . Nguyen Ngoc Thuy, N. Thuy, S. Wongthanavasu), IEEE Transactions on Neural Networks and Learning Systems, 33, 2022. [url] [doi]

[4]

Hybrid filter–wrapper attribute selection with alpha-level fuzzy rough sets ( . Nguyen Ngoc Thuy, N. Thuy, S. Wongthanavasu), Expert Systems with Applications, 193, 2022. [url] [doi]

[5]

A Hybrid Recommender System for Improving Rating Prediction of Movie Recommendation ( N. Kannikaklang, S. Wongthanavasu, W. Thamviset), 2022 19th International Joint Conference on Computer Science and Software Engineering, JCSSE 2022, , 2022. [url] [doi]

[6]

Sound and precise analysis of web applications for injection vulnerabilities ( C. Soomlek), Iot and AI Technologies for Sustainable Living A Practical Handbook, , 2022. [url] [doi]

[7]

Joint Opposite Selection (JOS): A premiere joint of selective leading opposition and dynamic opposite enhanced Harris’ hawks optimization for solving single-objective problems ( F. Arini, C. Soomlek, S. Chiewchanwattana, K. Sunat), Expert Systems with Applications, 188, 2022. [url] [doi]

[8]

Python Code Smell Detection Using Machine Learning ( C. Soomlek), Icsec 2022 International Computer Science and Engineering Conference 2022, , 2022. [url] [doi]

[9]

Golden Jackal Optimization with Joint Opposite Selection: An Enhanced Nature-Inspired Optimization Algorithm for Solving Optimization Problems ( F. Arini, K. Sunat, C. Soomlek), IEEE Access, 10, 2022. [url] [doi]

[10]

Thai Question-Answering System Using Pattem-Matching Approach ( C. Soomlek), Proceedings 2022 1st International Conference on Technology Innovation and Its Applications Ictiia 2022, , 2022. [url] [doi]

[1]

Enhanced Local Receptive Fields based Extreme Learning Machine using Dominant Patterns Selection ( P. Keawbor, P. Horata), ICSEC 2021 - 25th International Computer Science and Engineering Conference, , 2021. [url] [doi]

[2]

A novel temporal recommender system based on multiple transitions in user preference drift and topic review evolution ( C. Wangwatcharakul, S. Wongthanavasu), Expert Systems with Applications, 185, 2021. [url] [doi]

[3]

An improved cellular automata-based classifier with soft decision ( P. Wanna, S. Wongthanavasu), Journal of Internet Technology, 21, 2021. [url] [doi]

[4]

Assessing the ASEAN Smart Cities Network (ASCN) via the Quintuple Helix Innovation Framework, with Special Regard to Smart City Discourse, Civil Participation, and Environmental Performance ( S. Wongthanavasu), International Journal of Urban Sustainable Development, 13, 2021. [url] [doi]

[5]

Training needs assessment of the Royal Bhutan Police ( S. Wongthanavasu), Police Practice and Research, 22, 2021. [url] [doi]

[6]

การ พยากรณ์ ดัชนี หุ้น ตลาดหลักทรัพย์ แห่ง ประเทศไทย และ ดัชนี หุ้น บริษัท ป ต ท. สำรวจ และ ผลิต ปิโตรเลียม จำกัด (มหาชน) โดย เครือ ข่าย ความ เชื่อ เบ ส์ ( T. Chawlom, S. Wongthanavasu), KKU Research Journal (Graduate Studies) 21 (1), 162-179, 2021, , 2021. [url] [doi]

[7]

Automatic Human-Like Detection of Code Smells ( C. Soomlek, J. van Rijn, M. Bonsangue), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12986, 2021. [url] [doi]

[1]

An Incremental Kernel Extreme Learning Machine for Multi-Label Learning with Emerging New Labels ( Y. Kongsorot, P. Horata, P. Musikawan), IEEE Access, 8, 2020. [url] [doi]

[2]

An efficient stripped cover-based accelerator for reduction of attributes in incomplete decision tables ( . Nguyen Ngoc Thuy, N. Thuy, S. Wongthanavasu), Expert Systems with Applications, 143, 2020. [url] [doi]

[3]

Single Image Haze Removal Using Deep Cellular Automata Learning ( S. Tangsakul, S. Wongthanavasu), IEEE Access, 8, 2020. [url] [doi]

[4]

Dynamic Collaborative Filtering Based on User Preference Drift and Topic Evolution ( C. Wangwatcharakul, S. Wongthanavasu), IEEE Access, 8, 2020. [url] [doi]

[5]

SET index forecast using bayesian belief networks ( T. Chawlom, S. Wongthanavasu), KST 2020 - 2020 12th International Conference on Knowledge and Smart Technology, , 2020. [url] [doi]

[6]

A new approach for reduction of attributes based on stripped quotient sets ( . Nguyen Ngoc Thuy, N. Thuy, S. Wongthanavasu), Pattern Recognition, 97, 2020. [url] [doi]

[7]

Increasing the input data length of RSA cryptosystem by applying a hybrid lossless data compression algorithm ( C. Soomlek), Journal of Physics Conference Series, 1502, 2020. [url] [doi]

[8]

Building a needs-based curriculum in data science and artificial intelligence: Case studies in Indonesia, Sri Lanka, and Thailand ( C. Soomlek), International Symposium on Project Approaches in Engineering Education, 10, 2020. [url] [doi]

[9]

Enhancement of artificial emotional neural network using Jaya algorithm and the investigation of expanded feature selected for wind power forecasting ( S. Iamsa-At, P. Horata, K. Sunat), ACM International Conference Proceeding Series, , 2019. [url] [doi]

[10]

Kernel extreme learning machine based on fuzzy set theory for multi-label classification ( Y. Kongsorot, P. Horata, P. Musikawan, K. Sunat), International Journal of Machine Learning and Cybernetics, 10, 2019. [url] [doi]

[11]

Parallelized Metaheuristic-Ensemble of Heterogeneous Feedforward Neural Networks for Regression Problems ( P. Musikawan, P. Horata, K. Sunat, Y. Kongsorot, S. Chiewchanwattana), IEEE Access, 7, 2019. [url] [doi]

[12]

On reduction of attributes in inconsistent decision tables based on information entropies and stripped quotient sets ( . Nguyen Ngoc Thuy, N. Thuy, S. Wongthanavasu), Expert Systems with Applications, 137, 2019. [url] [doi]

[13]

Thailand Smart Cities: What is the Path to Success? ( S. Wongthanavasu), Asian Politics and Policy, 11, 2019. [url] [doi]

[14]

A Fast Convolutional Denoising Autoencoder Based Extreme Learning Machine ( J. Sawaengchob, P. Horata, P. Musikawan, Y. Kongsorot), ICSEC 2017 - 21st International Computer Science and Engineering Conference 2017, Proceeding, , 2018. [url] [doi]

[15]

Lagrangian Duality with ELM for Word Sense Multiprototype Discovery ( P. Liang, S. Wongthanavasu), Applied Artificial Intelligence, 32, 2018. [url] [doi]

[16]

Improving Single Image Haze Removal Based on Cellular Automata Model ( S. Tangsakul, S. Wongthanavasu), Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018, , 2018. [url] [doi]

[17]

Face Recognition in Unconstrained Environment ( W. Srisawasd, S. Wongthanavasu), Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018, , 2018. [url] [doi]

[18]

Improving Dynamic Recommender System Based on Item Clustering for Preference Drifts ( C. Wangwatcharakul, S. Wongthanavasu), Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018, , 2018. [url] [doi]

[19]

A Differential Evolution-based Rule Ordering of Cellular Automata for Classification ( P. Wanna, S. Wongthanavasu, P. Ponkaew), 2018 10th International Conference on Knowledge and Smart Technology: Cybernetics in the Next Decades, KST 2018, , 2018. [url] [doi]

[20]

Ensemble extreme learning machine for multi-instance learning ( S. Sastrawaha, P. Horata), ACM International Conference Proceeding Series, 0, 2017. [url] [doi]

[21]

An efficient brain tumor segmentation based on cellular automata and improved tumor-cut algorithm ( C. Sompong, S. Wongthanavasu), Expert Systems with Applications, 72, 2017. [url] [doi]

[22]

Foreword: Special issue for JCSSE 2016 ( B. Mishra, S. Peng, S. Wongthanavasu), Journal of Internet Technology, 18, 2017. [url] [doi]

[23]

Stochastic forward-looking prediction for entropy-based multimodal fused data ( P. Liang, S. Wongthanavasu), Journal of Internet Technology, 18, 2017. [url] [doi]

[24]

Tackling regional public health issues using mobile health technology: Event report of an mhealth hackathon in Thailand ( A. Pathanasethpong, C. Soomlek, K. Morley, P. Polpinit, A. Dagan, J. Weis, L. Celi), Jmir Mhealth and Uhealth, 5, 2017. [url] [doi]

[25]

Machine learning for SQL injection prevention on server-side scripting ( K. Kamtuo, C. Soomlek), 20th International Computer Science and Engineering Conference Smart Ubiquitos Computing and Knowledge Icsec 2016, , 2017. [url] [doi]

[26]

Performance analysis of video transmission over IEEE 802.11n wireless networks ( C. Soomlek), Journal of Telecommunication Electronic and Computer Engineering, 9, 2017. [url] [doi]

[27]

Improved convex incremental extreme learning machine based on ridgelet and PSO algorithm ( P. Musikawan, P. Horata, K. Sunat, S. Chiewchanwattana, Y. Kongsorot), 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016, , 2016. [url] [doi]

[28]

Extended hierarchical extreme learning machine with multilayer perceptron ( K. Phurattanaprapin, P. Horata), 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016, , 2016. [url] [doi]

[29]

Harmonic extreme learning machine for data clustering ( S. Boriratrit, S. Chiewchanwattana, K. Sunat, P. Musikawan, P. Horata), 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016, , 2016. [url] [doi]

[30]

Improvement flower pollination extreme learning machine based on meta-learning ( S. Boriratrit, S. Chiewchanwattana, K. Sunat, P. Musikawan, P. Horata), 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016, , 2016. [url] [doi]

[31]

Brain tumor segmentation using cellular automata-based fuzzy c-means ( C. Sompong, S. Wongthanavasu), 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016, , 2016. [url] [doi]

[32]

Least squared Itô's drift-diffusion Kernel function for fat tailed distribution simulation of realtime online stock price ( P. Liang, S. Wongthanavasu), 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016, , 2016. [url] [doi]

[33]

Hybrid linear matrix factorization for topic-coherent terms clustering ( P. Liang, S. Wongthanavasu), Expert Systems with Applications, 62, 2016. [url] [doi]

[34]

A cellular automata-based learning method for classification ( S. Wongthanavasu, P. Ponkaew), Expert Systems with Applications, 49, 2016. [url] [doi]

[35]

Subsequence-Based Dynamic Web Service Composition ( P. Liang, S. Wongthanavasu), International Journal of Future Computer and Communication 5 (4), 172, 2016, , 2016. [url] [doi]

[36]

ระบบ ให้ คำ แนะนำ ราย บุคคล เพื่อ การ วางแผน การ ท่องเที่ยว ( A. Namvong, S. Wongthanavasu), Information Technology Journal 12 (2), 24-32, 2016, , 2016. [url] [doi]

[37]

Automated detection of code smells caused by null checking conditions in Java programs ( K. Sirikul, C. Soomlek), 2016 13th International Joint Conference on Computer Science and Software Engineering Jcsse 2016, , 2016. [url] [doi]

[38]

Using backpropagation neural networks for flood forecasting in PhraNakhon Si Ayutthaya, Thailand ( C. Soomlek, N. Kaewchainam, T. Simano, C. So-In), Icsec 2015 19th International Computer Science and Engineering Conference Hybrid Cloud Computing A New Approach for Big Data Era, , 2016. [url] [doi]

[39]

Enhancement of online sequential extreme learning machine based on the householder block exact inverse QRD recursive least squares ( P. Horata, S. Chiewchanwattana, K. Sunat), Neurocomputing, 149, 2015. [url] [doi]

[40]

Evolutionary circular-ELM for the reduced-reference assessment of perceived image quality ( S. Atsawaraungsuk, P. Horata), Lecture Notes in Electrical Engineering, 339, 2015. [url] [doi]

[41]

Applying regularization least squares canonical correlation analysis in extreme learning machine for multi-label classification problems ( Y. Kongsorot, P. Horata, K. Sunat), Proceedings of ELM-2014 Volume 1: Algorithms and Theories, 377-396, 2015, , 2015. [url] [doi]

[42]

Facial age estimation using a hybrid of SVM and Fuzzy Logic ( P. Hadchum, S. Wongthanavasu), ECTI-CON 2015 - 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, , 2015. [url] [doi]

[43]

Applying randori-style kata and agile practices to an undergraduate-level programming class ( C. Soomlek), Lecture Notes in Business Information Processing, 212, 2015. [url] [doi]

[44]

License plate recognition application using extreme learning machines ( S. Subhadhira, U. Juithonglang, P. Sakulkoo, P. Horata), Proceedings of the 2014 3rd ICT International Senior Project Conference, ICT-ISPC 2014, , 2014. [url] [doi]

[45]

Multi-label classification with extreme learning machine ( Y. Kongsorot, P. Horata), Proceedings of the 2014 6th International Conference on Knowledge and Smart Technology, KST 2014, , 2014. [url] [doi]

[46]

Improving butterfly family classification using past separating features extraction in extreme learning machine ( P. Horata, S. Iamsa-ata, P. Horataa, K. Sunata, N. Thipayanga), Proceedings of the 2nd International Conference on Intelligent Systems and …, 2014, , 2014. [url] [doi]

[47]

Forecasting number of dengue patients using cellular automata model ( T. Soemsap, S. Wongthanavasu, W. Satimai), 2014 International Electrical Engineering Congress, iEECON 2014, , 2014. [url] [doi]

[48]

Cellular Automata learning algorithm for classification ( S. Wongthanavasu, P. Ponkaew), 2014 International Electrical Engineering Congress, iEECON 2014, , 2014. [url] [doi]

[49]

Speech recognition - Based control system for Drone ( S. Supimros, S. Wongthanavasu), Proceedings of the 2014 3rd ICT International Senior Project Conference, ICT-ISPC 2014, , 2014. [url] [doi]

[50]

Information extraction for deep web using repetitive subject pattern ( W. Thamviset, S. Wongthanavasu), World Wide Web, 17, 2014. [url] [doi]

[51]

Bottom-up region extractor for semi-structured web pages ( W. Thamviset, S. Wongthanavasu), 2014 International Computer Science and Engineering Conference, ICSEC 2014, , 2014. [url] [doi]

[52]

Image cellular automata coding based on resolution progressive experiments with color spaces and file formats ( P. Claiboon, S. Wongthanavasu), 2014 International Computer Science and Engineering Conference, ICSEC 2014, , 2014. [url] [doi]

[53]

MRI brain tumor segmentation using GLCM cellular automata-based texture feature ( C. Sompong, S. Wongthanavasu), 2014 International Computer Science and Engineering Conference, ICSEC 2014, , 2014. [url] [doi]

[54]

An efficient Cellular Automata-based error-correcting capability ( P. Ponkaew, S. Wongthanavasu, C. Lursinsap), Information (Japan), 17, 2014. [url] [doi]

[55]

Scalable resolution-based image coding algorithm ( P. Claiboon, S. Wongthanavasu), 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, , 2014. [url] [doi]

[56]

A novel segmentation method for isointense MRI brain tumor ( C. Sompong, S. Wongthanavasu), 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, , 2014. [url] [doi]

[57]

Medical diagnosis model using cellular automata-based image processing and bayesian belief network ( S. Wongthanavasu, V. Tangvoraphongchai), Thailand Science Research and Innovation, 2014, , 2014. [url] [doi]

[58]

Data Regions Extraction for Semi-Structured Web Pages Using Bottom-up Approach (การ สกัด พื้นที่ ข้อมูล จาก หน้า เว็บ กึ่ง โครงสร้าง โดย ใช้ วิธี การ แบบ ล่าง ขึ้น บน) ( W. Thamviset, S. Wongthanavasu), KKU Research Journal (Graduate Studies) 14 (4), 1-16, 2014, , 2014. [url] [doi]

[59]

Improvement Query In And Reserch Database Using Particle Swarm Optimization ( P. Horata, ส. พรมบุญเรือง, ป. หอระตะ, ค. สุนัติ, ส. เชี่ยวชาญวัฒนา), Kasetsart Engineering Journal, 27, 2014. [url] [doi]

[60]

Agent-based wellness indicator ( C. Soomlek), Healthcare Administration Concepts Methodologies Tools and Applications, 2, 2014. [url] [doi]

[61]

MAP: An optimized energy-efficient cluster header selection technique for wireless sensor networks ( C. Soomlek), Lecture Notes in Electrical Engineering, 279, 2014. [url] [doi]

[62]

Handwritten character recognition using histograms of oriented gradient features in deep learning of artificial neural network ( S. Iamsa-At, P. Horata), 2013 International Conference on IT Convergence and Security, ICITCS 2013, , 2013. [url] [doi]

[63]

Evolutionary circular extreme learning machine ( S. Atsawaraungsuk, P. Horata, K. Sunat, S. Chiewchanwattana, P. Musigawan, .. ), 2013 International Computer Science and Engineering Conference, ICSEC 2013, , 2013. [url] [doi]

[64]

Robust extreme learning machine ( P. Horata, S. Chiewchanwattana, K. Sunat), Neurocomputing, 102, 2013. [url] [doi]

[65]

Speech emotion recognition using support vector machines ( T. Seehapoch, S. Wongthanavasu), Proceedings of the 2013 5th International Conference on Knowledge and Smart Technology, KST 2013, , 2013. [url] [doi]

[66]

Cellular automata for pattern recognition ( S. Wongthanavasu, P. Ponkaew), Emerging Applications of Cellular Automata, 53-67, 2013, , 2013. [url] [doi]

[67]

An agent-based wellness indicator: Experimental results and future directions ( C. Soomlek, L. Benedicenti), Journal of Information Technology Research, 6, 2013. [url] [doi]

[68]

Structured web information extraction using repetitive subject pattern ( W. Thamviset, S. Wongthanavasu), 2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2012, , 2012. [url] [doi]

[69]

A comparative study of pseudo-inverse computing for the extreme learning machine classifier ( P. Horata, S. Chiewchanwattana, K. Sunat), Proceedings - 3rd International Conference on Data Mining and Intelligent Information Technology Applications, ICMIA 2011, , 2011. [url] [doi]

[70]

A nonlinear classifier using an evolution of Cellular Automata ( P. Ponkaew, S. Wongthanavasu, C. Lursinsap), 2011 International Symposium on Intelligent Signal Processing and Communications Systems: "The Decade of Intelligent and Green Signal Processing and Communications", ISPACS 2011, , 2011. [url] [doi]

[71]

Two-class classifier cellular automata ( P. Ponkaew, S. Wongthanavasu, C. Lursinsap), 2011 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2011, , 2011. [url] [doi]

[72]

Cellular automata for medical image processing ( S. Wongthanavasu), Cellular Automata-Innovative Modelling for Science and Engineering, 395-410, 2011, , 2011. [url] [doi]

[73]

A Bayesian Belief Network Model for Breast Cancer Diagnosis ( S. Wongthanavasu), Operations Research Proceedings 2010: Selected Papers of the Annual …, 2011, , 2011. [url] [doi]

[74]

Creating a Framework for Testing Wellness Visualization Systems ( C. Soomlek, L. Benedicenti), PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON EHEALTH, TELEMEDICINE, AND SOCIAL MEDICINE (ETELEMED 2011), , 2011. [url] [doi]

[75]

Operational wellness model: A wellness model designed for an agent-based wellness visualization system ( C. Soomlek, L. Benedicenti), 2nd International Conference on Ehealth Telemedicine and Social Medicine Etelemed 2010 Includes Mlmb 2010 Busmmed 2010, , 2010. [url] [doi]

Reference (APA)

Publications (In the Last 5 Years)

2026

2025

[1]

[2]

[3]

[4]

2024

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

2023

[1]

[2]

[3]

[4]

[5]

2022

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

2021

[1]

[2]

[3]

[4]

[5]

[6]

[7]

Before 2020

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

[19]

[20]

[21]

[22]

[23]

[24]

[25]

[26]

[27]

[28]

[29]

[30]

[31]

[32]

[33]

[34]

[35]