Prapa Rattadilok

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This paper investigates an emerging class of search algorithms, in which high-level domain independent heuristics, called hyperheuristics, iteratively select and execute a set of application specific but simple search moves, called low-level heuristics, working toward achieving improved or even optimal solutions. Parallel architectures have been designed(More)
The paper proposes a generic approach to building inferential measurement systems. The large amount of data needed to be acquired and processed by such systems necessitates the use of machine learning techniques. In this study, an inferential measurement system aimed at enhancing situation awareness has been developed and tested on simulated traffic(More)
Real-time data processing has become an increasingly important challenge as the need for faster analysis of big data widely manifests itself. In this research, several methods of Computational Intelligence have been applied for identifying possible anomalies in two datasets. The proposed framework shows a promising potential for anomaly detection and its(More)
An adaptive multi-tiered framework, which can be utilised for designing a context-aware cyber physical system is proposed in the paper and is applied within the context of providing data availability by monitoring electromagnetic interference. The adaptability is achieved through the combined use of statistical analysis and computational intelligence(More)
A generic framework for evolving and autonomously controlled systems has been developed and evaluated in this paper. A three-phase approach aimed at identification, classification of anomalous data and at prediction of its consequences is applied to processing sensory inputs from multiple data sources. An ad-hoc activation of sensors and processing of data(More)
An adaptive inferential measurement framework for control and automation systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making inferences related to the presence of anomalies in the surveillance data with the help of statistical, computational and clustering analysis. Moreover, the(More)
The need to assess internet performance from the user's perspective grows, as does the interest in deployment of Large-Scale Measurement Platforms (LMAPs). The potential of these platforms as a real-time network diagnostic tool is limited by the volume, velocity and variety of the data they generated. Fusing this data from multiple sources and generating a(More)
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