Sooraksa, Pitikhate

Preferred name

Sooraksa, Pitikhate

Alternative Name

Sooraksa, P.

Main Affiliation

School of Engineering

pitikhate.so@kmitl.ac.th

Now showing 1 - 10 of 22

Some of the metrics are blocked by your
consent settings
Naphtha's price forecasting using neuro-fuzzy system
(2008-12-01)
Visetsripong, Porntip
;
Sooraksa, Pitikhate
;
Luenam, Pramote
;
Chaimongkol, Watchareeporn
Naphtha's price forecasting using Neuro-fuzzy system is a forecasting technique that applied information technology with statistics. 1950 daily prices were collected as a time-series data with trend component. The research found that Neuro-Fuzzy system is more accurate and more reliable than a statistical method; it also works well with continuous data and performs better with more training data. Neuro-Fuzzy system might be used with different data type, but, it might come across with other factors, e.g. seasonal or irregular event. The research also illustrates the multidisciplinary nature in today's world of works in the era of merging among many disciplines. © 2008 SICE.
Some of the metrics are blocked by your
consent settings
Combined chaotic attractor mobile robots
(2006-12-01)
Chanvech, Channawat
;
Klomkarn, Kitdakorn
;
Sooraksa, Pitikhate
The application of chaos in engineering field has been attracted much attention due to many potential applications include fan heaters, air-conditions, and dish washing machines. Even though the applied chaos in robot guidance is also not new, the problem of navigation of autonomous mobile robot in a totally unknown environment can be accomplished by using chaotic function. For implementation, most of researchers use CPUs with high performance to generate the chaotic trajectory. Unlike the others, in this paper, we use a chaotic circuit, which is low cost and easy to construct for trajectory generators. The Chua's circuit and a complex butterfly attractor are combined together providing pattern diversity and area coverage. A lab-scale two-wheel mobile robot is implemented and tested in our laboratory. The experimental results confirm that the proposed scheme of combined chaotic attractors is effective for path guiding for chaotic mobile robots. © 2006 ICASE.
Some of the metrics are blocked by your
consent settings
Improvement of state estimation for systems with chaotic noise
(2008-12-01)
Sooraksa, Pitikhate
;
Jandaeng, Prakob
To estimate the state of the system, one needs the covariance matrices as the inputs. The accuracy of the new prediction of the estimation is based recursively on the previous ones. To search for the optimal solution, researchers try to obtain best closed-state approximation for the covariance inputs using the Kalman filtering technique. Many variations of the technique have been proposed for many years. However, in this chapter, our version presents a new improvement of state estimation of the systems with various chaotic noises. Introducing an updated scaling factor to the covariance matrices is a simple modification yet provides a highly effective way to estimate the state of the system in the presence of chaotic noises. Performance comparison among the original Kalman filter, an adaptive version, and our enhanced one is carried out. Computer simulation shows remarkable improvement of the proposed method for estimation of the state of the systems with chaotic noises. © 2008 Springer Science+Business Media, LLC.
Some of the metrics are blocked by your
consent settings
On comparison of attractors for chaotic mobile robots
(2004-12-01)
Jansri, Anurak
;
Klomkarn, Kitdakorn
;
Sooraksa, Pitikhate
In case of no map, trajectory planning could be a difficult task for robot motions to navigate around the assigned patrol areas. Chaotic mobile robots that move in chaotic patterns can be used to solve this problem. This paper is motivated by the question in seeking for suitable chaotic pattern for the aforementioned problem. Twenty-five chaotic patterns generated from various chaotic signals for the robot's path are compared by computer simulation under given conditions. © 2004 IEEE.
Some of the metrics are blocked by your
consent settings
On Comparison of Hybrid Fuzzy PI Plus Conventional D Controller Versus Fuzzy PI+D Controller
(2004-02-01)
Sooraksa, Pitikhate
;
Chen, Guanrong
This letter points out that a comparison given in an earlier paper by Er and Sun is incorrect. The fuzzy PI+D controller designed by Misir et al. is overall better than the hybrid fuzzy PI plus conventional D controller designed by Er and Sun.
Some of the metrics are blocked by your
consent settings
A geno-hydra control system: Design and tuning hybrid controller based on hydra control structure by using genetic algorithms
(2006-12-01)
Sanornoi, Nitiwat
;
Purahong, Boonchana
;
Sritheerawirojana, Uthai
;
Sooraksa, Pitikhate
This paper shows how to design the hybrid control system based on hydra control structure by introducing two design strategies which are as following: Double head and Line up. These two strategies use Genetic Algorithms to improve parameters in control system and they also situate the Challenge and Best-selection processes which are the methods to compare the efficiency of the system after they have been genetically calculated. In order to select an appropriate control system in each layer, the simulation's results in the end will show the test with Non-linear plant to show the efficiency of control system after it has been developed by designing and tuning process. © 2006 IEEE.
Some of the metrics are blocked by your
consent settings
Artificial intelligence based on fuzzy behavior for game programming
(2004-01-01)
Sanornoi, Nitiwat
;
Sooraksa, Pitikhate
This paper applies the behavior-based control for mobile robots to design the artificial-intelligent characteristics of game programming in order to reduce the complexity of the intelligence features of the enemies in a game. The artificial intelligence in this paper composes of fuzzy system for creation of the natural behavior. This fuzzy model employs Takagi-Sugeno's methodology for building program modules. The character described in the model herein is the enemy of 'Mage in the Demon Zone' game. Copyright 2004 ACM.
Some of the metrics are blocked by your
consent settings
Further investigation on trajectory of chaotic guiding signals for robotic systems
(2004-12-01)
Jansri, Anurak
;
Klomkarn, Kitdakorn
;
Sooraksa, Pitikhate
Chaotic signals have been used and can be generated by a chaotic circuit for controlling trajectories of mobile robots. Application of chaotically robotic systems may be employed for cleaning and patrolling tasks, when information of areas at work is not available. This paper presents an investigation on trajectory of chaotic guiding signals generated by Chua's attractor and Arnold's non-attractor in five given situations. According to the simulation, with best adjusting parameters for both signals, the trajectory generated from Chua's pattern has covered more areas than that of Arnold's counterpart for all testing cases.
Some of the metrics are blocked by your
consent settings
A new hybrid fuzzy proportional-derivative phase-locked-loop controller for DC servomotor speed control
(2007-08-01)
Sooraksa, Pitikhate
;
Li, Chung Wai
;
Damrongporn, Phuwanat
Some research work has been heading to the promising direction of enhancing conventional controllers with various powerful intelligent features. In this pursuit, the paper presents a new fuzzy-based phase-locked loop (FPLL) controller for DC servomotor speed control. Fuzzy logic provides fast response and enhances robustness of the system while PLL control gives excellent steady state system performance. Unlike the past literatures, this fuzzy-based controller employs a proportional-derivative (FPD) controller, which is constructed precisely based on rigorous mathematical analysis instead of using look-up tables, with stability guaranteed. Simulation and experimental results have signified the design objectives and been accomplished. The proposed new fuzzy-based PLL controller gives a better dynamic performance compared to a conventional PID controller. Copyright © 2007 Watam Press.
Some of the metrics are blocked by your
consent settings
Credit scoring using least squares support vector machine based on data of Thai financial institutions
(2007-07-03)
Worrachartdatchai, Usanee
;
Sooraksa, Pitikhate
The quantitative method known as credit scoring has been developed for the credit assessment problem. Credit scoring is essentially an application of classification techniques, which classify credit customers into different risk groups. The Financial institutions are being more and more obliged to build credit scoring models assessing the risk of default of their clients. Support Vector Machine is a promising new technique that has recently emanated and become popular for data classification. Least Squares Support Vector Machines (LS-SVM) are re-formulations to the standard SVMs. The cost function is a regularized least squares function with equality constraints. The solution can be found efficiently by iterative method like the conjugate Gradient algorithm. Then in this paper, Least Squares Support Vector Machine is considered by approaching to the credit scoring with the data of Thai financial institutions. The optimum model will be able to divide the group of customers into four groups: very good, rather good, suspiciously bad and very bad with high accuracy.

Sooraksa, Pitikhate

Filters

Settings

Sort By

Results per page