Search Results
A hybrid forecasting model of cassava price based on artificial neural network with support vector machine technique
Polyiam, Korawat, Boonrawd, Pudsadee (2017)
of cassava price based on the 11-year data (from 2005 to 2015) obtained from the Thai Tapioca Starch Association and Office of Agricultural Economics. Various techniques were applied for the forecast such as Artificial Neural Network; Support Vector Machine... that Hybrid Technique demonstrated the lowest value of error followed by Artificial Neural Network; k-Nearest Neighbor and Support Vector Machine; respectively. Therefore; it could be concluded that using the Hybrid Technique to forecast the price of cassava
Comparison of prediction models for road deaths on road network
Whasphutthisit, Thaninthorn, Jitsakul, Watchareewan (2022)
Neighbor (KNN); and Neural Network (NN). The dead injured and dead people data in road accident data set of the Ministry of Transport; Thailand from January to April 2021. It has up to 8;560 records 46 attributes. This research has measured performance...This paper presents to compare prediction models for road deaths on road network by data mining techniques. In this work; the classifier is selected from four prediction algorithms: Random Forest (RF); Support Vector Machine (SVM); K-Nearest
Multi-language communication protocol model based on conceptual spaces and language games | Interdisciplinary Research Review
Juntarajessadakorn, Somjin, Nuipian, Vatinee, Meesad, Phayung (2018)
a conceptual model based on Language Games and Self- Organizing Map neural networks. In addition; the model proposed includes an important feature that is a dynamic radius for multi-languages communicative interactions between autonomous agents. We...Interacting artificial intelligent systems need to understand human language. This paper demonstrates how artificial systems can learn and communicate with each other in three different languages: Thai; Chinese; and English. In this work; we extend
Classification of bus stopping prediction using deep artificial neural network on GNSS-based bus tracking data
Posawang, Pitiphum, Phosaard, Satidchoke, Pattara-atikom, Wasan (2017)
Comparing local descriptors and bags of visual words to deep convolutional neural betworks for plant recognition
Pawara, Pornntiwa, Okafor, Emmanuel, Surinta, Olarik, Schomaker, Lambert (2017)
classifiers to deep convolutional neural networks (CNNs) on three plant datasets; AgrilPlant; LeafSnap; and Folio. To achieve this; we study the use of both scratch and fine-tuned versions of the GoogleNet and the AlexNet architectures and compare them to a
A face recognition system using open face and self-organizing incremental neural networks
Talasee, J., Sangkaew, C. (2019)
Multi-language communication protocol model based on conceptual spaces and language games
Juntarajessadakorn, Somjin, Nuipian, Vatinee, Meesad, Phayung (2018)
a conceptual model based on Language Games and Self- Organizing Map neural networks. In addition; the model proposed includes an important feature that is a dynamic radius for multi-languages communicative interactions between autonomous agents. We...Interacting artificial intelligent systems need to understand human language. This paper demonstrates how artificial systems can learn and communicate with each other in three different languages: Thai; Chinese; and English. In this work; we extend