Pannakkong, W., Vinh, V. T., Tuyen, N. N. M., & Buddhakulsomsiri, J. (2023). A Reinforcement Learning Approach for Ensemble Machine Learning Models in Peak Electricity Forecasting. Energies, 16(13), 5099.

 

Saophan, P., Pannakkong, W., Singhaphandu, R., & Huynh, V. N. (2023). Rapid Production Rescheduling for Flow Shop under Machine Failure Disturbance Using Hybrid Perturbation Population Genetic Algorithm-Artificial Neural Networks (PPGA-ANNs). IEEE Access.

 

Aswanuwath, L., Pannakkong, W., Buddhakulsomsiri, J., Karnjana, J., & Huynh, V. N. (2023). A Hybrid Model of VMD-EMD-FFT, Similar Days Selection Method, Stepwise Regression, and Artificial Neural Network for Daily Electricity Peak Load Forecasting. Energies, 16(4), 1860.

 

Ji, J., Pannakkong, W., & Buddhakulsomsiri, J. (2023). A Computer Vision-Based System for Metal Sheet Pick Counting. Computers, Materials & Continua, 75(2).

 

Tanantong, T., Pannakkong, W., & Chemkomnerd, N. (2022). Resource management framework using simulation modeling and multi-objective optimization: a case study of a front-end department of a public hospital in Thailand. BMC Medical Informatics and Decision Making, 22(1), 1-21.

 

Pannakkong, W., Parthanadee, P., & Buddhakulsomsiri, J. (2022). Impacts of harvesting age and pricing schemes on economic sustainability of cassava farmers in Thailand under market uncertainty. Sustainability, 14(13), 7768.

 

Pannakkong, W., Harncharnchai, T., & Buddhakulsomsiri, J. (2022). Forecasting daily electricity consumption in Thailand using regression, artificial neural network, support vector machine, and hybrid models. Energies, 15(9), 3105.

 

Ji, J., Pannakkong, W., & Buddhakulsomsiri, J. (2022). A Computer Vision-Based Model for Automatic Motion Time Study. Computers, Materials & Continua, 73(2).

Pannakkong, W., Thiwa-Anont, K., Singthong, K., Parthanadee, P., & Buddhakulsomsiri, J. (2022). Hyperparameter tuning of machine learning algorithms using response surface methodology: a case study of ANN, SVM, and DBN. Mathematical problems in engineering, 2022, 1-17.

 

Ji, J., Pannakkong, W., & Buddhakulsomsiri, J. (2022). A Computer Vision-Based Model for Automatic Motion Time Study. Computers, Materials & Continua, 73(2).

 

Saophan, P., & Pannakkong, W. (2022, March). A Genetic Algorithm Based Artificial Neural Network for Production Rescheduling Problem. In International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (pp. 279-290). Cham: Springer International Publishing.

 

Ananvaithayakij, N., & Pannakkong, W. (2022). An automatic warehouse inventory monitoring system based on text extraction using computer vision (Doctoral dissertation, Thammasat University).

 

Tiwari, S., & Pannakkong, W. (2022). An intelligence system for a car-carrier loading optimization (Doctoral dissertation, Thammasat University).

 

Chaimongkol, O., & Pannakkong, W. (2022). A computer vision-based counting system: a case study of rubber grommet (Doctoral dissertation, Thammasat University).

 

Sadakorn, P., & Pannakkong, W. (2022). DEMAND FORECASTING BY MACHINE LEARNING (CASE STUDY OF ACRYLIC PRODUCTS) (Doctoral dissertation, Thammasat University).

 

Boonsem, T., Pannakkong, W., & Buddhakulsomsiri, J. (2022). Surface defect detection in lime by using computer vision(Doctoral dissertation, Thammasat University).

 

Pannakkong, W., Thi, K. C. V., & Olapiriyakul, S. (2021, June). Towards a Socially Sustainable Inventory Optimization. In 18th International Symposium on Management (INSYMA 2021) (pp. 139-145). Atlantis Press.

 

Vinh, V. T., Pannakkong, W., & Buddhakulsomsiri, J. (2021). Implement tuned reinforcement learning in selecting different machine learning models prediction for peak electricity consumption (Doctoral dissertation, Thammasat University).

 

Chaiwong, N., Pannakkong, W., & Buddhakulsomsiri, J. (2021). Classifying saleability of lime by using convolutional neural network (CNN) approach (Doctoral dissertation, Thammasat University).

 

Kittitharayada, P., Buddhakulsomsiri, J., & Pannakkong, W. (2021). Using design of experiments during the process of tuning hyperparameters in machine learning algorithms(Doctoral dissertation, Thammasat University).

 

Chunvirat, M. S., & Pannakkong, W. (2021). A smart warehouse for small to medium enterprise with an integration of internet of things, artificial intelligence, and computer vision(No. 190333). Thammasat University.

 

Aphisakulchat, M. N., & Pannakkong, W. (2021). Modified decision tree model for fraud detection application (Doctoral dissertation, Thammasat University).

 

Tongmungkorn, C., & Pannakkong, W. (2021). Forecasting hotel room cancellations by using machine learning (Doctoral dissertation, Thammasat University).

 

Sirichartchai, A., & Pannakkong, W. (2021). Forecasting patient length of stay in hospital using machine learning algorithm (Doctoral dissertation, Thammasat University).

 

Maitreesorasuntee, C., Jeenanunta, C., Buddhakulsomsiri, J., Pannakkong, W., Chaysiri, R., Masahiro, N., & Karnjana, J. (2020). A Steel Tube Production Planning and Scheduling with Product-Dependent Changeover Time Using Digital Twin. INTERNATIONAL SCIENTIFIC JOURNAL OF ENGINEERING AND TECHNOLOGY (ISJET), 4(2), 13-19.

 

Thiwa-anont, K., Buddhakulsomsiri, J., & Pannakkong, W. (2020, April). Raw Material Characteristic Prediction for Packing Media Preparation in Canned Pineapple Production Line. In 2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA) (pp. 350-354). IEEE.

 

Sasanarakkij, J., & Pannakkong, W. (2020). Job scheduling and packing optimization in warehouse: on-time order delivery and incentive for full-pack order (Doctoral dissertation, Thammasat University).

 

Ji, J., Pannakkong, W., Tai, P. D., Jeenanunta, C., & Buddhakulsomsiri, J. (2020). Motion time study with convolutional neural network. In Integrated Uncertainty in Knowledge Modelling and Decision Making: 8th International Symposium, IUKM 2020, Phuket, Thailand, November 11–13, 2020, Proceedings 8 (pp. 249-258). Springer International Publishing.

 

Singhaphandu, R., Huynh, V. N., & Pannakkong, W. (2020). Analysis and Feedback of Movement in Manual Assembly Process. In Advances in the Human Side of Service Engineering: Proceedings of the AHFE 2020 Virtual Conference on The Human Side of Service Engineering, July 16-20, 2020, USA (pp. 265-270). Springer International Publishing.

 

Pannakkong, W., Aswanuwath, L., Buddhakulsomsiri, J., Jeenanunta, C., & Parthanadee, P. (2019, November). Forecasting medium-term electricity demand in Thailand: Comparison of ANN, SVM, DBN, and their ensembles. In 2019 17th International Conference on ICT and Knowledge Engineering (ICT&KE) (pp. 1-6). IEEE.

 

Pannakkong, W., Chemkomnerd, N., & Tanantong, T. (2019, November). Simulation Analysis of University Hospital in the Medical Record Department. In 2019 17th International Conference on ICT and Knowledge Engineering (ICT&KE)(pp. 1-6). IEEE.

 

Phonwiphat, P., Pannakkong, W., Yenradee, P., Ekkachai, K., & Takahashi, A. (2019, July). An Intelligent System for Identifying Feasible Routes for Truck Routing Problem: An Application to a Thai Adhesive and Sealant Company (ATASC). In 2019 16th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) (pp. 905-910). IEEE.

 

Olapiriyakul, S., Pannakkong, W., Kachapanya, W., & Starita, S. (2019). Multiobjective optimization model for sustainable waste management network design. Journal of Advanced Transportation, 2019.

 

Ou, M. S., & Pannakkong, W. (2019). Assessment of rooftop solar photovoltaic potential in Thailand: a case study of an industrial estate (Doctoral dissertation, Thammasat University).

 

Aswanuwath, L., & Pannakkong, W. (2019). Forecasting medium-term electricity demand in Thailand using machine learning (Doctoral dissertation, Thammasat University).

 

Chemkomnerd, M. N., Pannakkong, W., & Tanantong, T. (2019). Simulation modelling and analysis of multiple classes of patient flow: a case of university hospital (Doctoral dissertation, Thammasat University).

 

Pannakkong, W., Huynh, V. N., & Sriboonchitta, S. (2019). A novel hybrid autoregressive integrated moving average and artificial neural network model for cassava export forecasting. International Journal of Computational Intelligence Systems, 12(2), 1047-1061.

 

Buddhakulsomsiri, J., Parthanadee, P., & Pannakkong, W. (2018). Prediction models of starch content in fresh cassava roots for a tapioca starch manufacturer in Thailand. Computers and Electronics in Agriculture, 154, 296-303.

 

Pannakkong, W., Sriboonchitta, S., & Huynh, V. N. (2018). An ensemble model of arima and ann with restricted boltzmann machine based on decomposition of discrete wavelet transform for time series forecasting. Journal of Systems Science and Systems Engineering, 27, 690-708.

 

Maitreesorasunte, C., Tang, J., Chaysiri, R., Jeenanunta, C., Pannakkong, W., Vitharana, H., & Parthanadee, P. (2018, July). Forecasting self-consumption solar power capacity of industry and business sector in Thailand: a system dynamic model. In 2018 2nd International Conference on Engineering Innovation (ICEI) (pp. 111-116). IEEE.

Saophan, M. P., & Pannakkong, W. (2018). Forecasting solar power for self-consumption of households in Thailand using system dynamics model (Doctoral dissertation, Thammasat University).