Markov Decision Process in no-data Problem based on Probabilitic Differental Equation in Fuzzy Events

Abstract

Tanaka et al formulated the fuzzy-Bayes decision making rule by integral transformation based on the expected utility maximization theory as an extension to Wald's subjective modification fuzzy event. Hori et al formulated the fuzzy ยท Bayes decision making rule which extended Wald's decision function to fuzzy OR combination and fuzzy AND combination with many subjective distribution. This decision-making law is based on the state of nature Is a decision-making rule after mapping and conversion to fuzzy events, and it is an OR type 2 fuzzy by mapping fuzzy functions such as subjective distribution and utility functions to fuzzy events. Furthermore, Hori introduced the Markovian time concept to the state of nature, and derived the Markov process and Markov decision process in fuzzy events. This is a natural extension to the stochastic process theory of Wald's decision function, and the fuzzy event of appearance of the natural state becomes a Markov process having a fuzzy transition matrix, and as a result of the Monte Carlo simulation, the annihilation, reversal, resurrection Repeat the cycle. Finally, Hori et al proposed an illusion state identification method as an example of adaptation of these fuzzy / Bayes decision making rules. In addition, Hori et al. Firstly used the max product method by mapping / transformation of membership functions of fuzzy events in a fuzzy event in which the subjective distribution and utility function in the no data problem transit like ergodic Markov We formulated these Markov decision processes. Note that this series of flows is a natural extension to the stochastic process of Wald's decision function. Next, we consider subjective distribution and utility function as fuzzy functions, subjectivity maps / converts natural state by subjective distribution, utility assumes that natural state is mapped / converted by utility function, The subjectivity and the utility also showed that it follows Markov process. Finally, the subjectivity and utility in fuzzy events were propagated by Markov processes in which each element of the transition matrix follows the Markov process, and proposed the Markov decision process by the Max product method

Authors and Affiliations

Hori Houju Jr, Kazuhisa Takemura, Yukio Matsumoto

Keywords

Related Articles

Thermal Analysis of Laptop Battery Using Composite Material

The main objective of this paper is to reduce the heat produced in the Battery. A composite material is placed over the battery to absorb the heat produced in the internal cells and outer casing. The temperature of the b...

Comparitive Analysis of Fuzzy Based MPPT for Boost and SEPIC Converter Topologies for PV Application

This paper proposes the Maximum Power Point Tracking based on Fuzzy logic control for PV System.MPPT is required to extract maximum power corresponding to specific operating point. The output power of PV System is depend...

Enhancing the Performance of P3HT/Cdse Solar Cells by Optimal Designing of Active Layer

The present study examined the influence of different condition like as doping , in active layer, on the performance of P3HT/CdSe Solar cells .In this work, we analyzed the best doping for the configuration of P3HT/ CdSe...

Sustainable Biodiesel Reactor Prototype Energetically Powered By Solar Energy

The study of routes aiming the implementation and use alternative energy sources has increased exponentially during the last decades, due to reduction of petroleum reserves and environmental damage related to fossil fuel...

Interpretation of the Operation Modes of the Doubly Fed Induction Machine in Wind Energy Systems

Over the last years, there has been a strong penetration of renewal energy sources into the power supply network. Wind energy generation has played and will continue to play a very important role in this area for the com...

Download PDF file
  • EP ID EP388413
  • DOI 10.9790/1676-1206014960.
  • Views 140
  • Downloads 0

How To Cite

Hori Houju Jr, Kazuhisa Takemura, Yukio Matsumoto (2017). Markov Decision Process in no-data Problem based on Probabilitic Differental Equation in Fuzzy Events. IOSR Journals (IOSR Journal of Electrical and Electronics Engineering), 12(6), 49-60. https://europub.co.uk/articles/-A-388413