Analytic Hierarchy Process (AHP) is one of the most popular tools for supporting human decision making, and several fuzzy extensions of AHP have been proposed. The present paper discusses psychological effects of both fuzzy rating and crisp feedback of the results in fuzzy AHP. Fuzzy rating in fuzzy AHP could incorporate the fuzziness of a person's feelings in his/her decision making. Crisp feedback, which exaggerates the superiority of only one alternative or the differences among the alternatives, could help a person make his/her decision, especially when being deeply puzzled about his/her choice. The paper suggests that using both fuzzification and defuzzification in fuzzy AHP is very important for supporting human decision making.

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[in Japanese]

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[in Japanese]

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Bilattices are one of algebraic structures and have had an extensive use in recent years, most notably in the area of logic programming. These structures are also useful as a semantic tool for defining multi-valued logics. Many properties of bilattices' are strongly related to non-monotone reasoning, and especially suitable for reasoning in the presence of inconsistency. In this paper, we discuss the interlacing condition of bilattices' and give some new sufficient conditions for bilattices not to be interlaced.

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In this paper, we propose a new intrusion detection method that is based on the characteristics of command chains used in an interactive computer environment. The frequency of the commands inputted by a user in a period is analyzed and the user model is constructed. The user authentication system gives warning when the frequency distribution of command chains is not alike comparing with the user model created in the past. We have already proposed a method constructing the user model based on the command chain probability, i.e, the transition probability from the command to the next command in the chain. In this paper, we propose a new method in which the fuzzy measure is used instead of the command chain probability. In order to examine the validity of the method, we reported here the results of the simulation experiment applying the method to the UNIX shell command log data of users. The experiment consists of the two phases, the learning phase, and the test phase. In the learning phase, a user model is generated as for a proper user. The user model consists of the grade of command chain which is defined as the fuzzy measure. In this method, when the frequency of the command chain is high, the grade of the command chain in the learning phase is higher than in the former method. In the test phase, the attestation judgment whether a user is the proper user or not is performed using the combination grades of command chain by the Choquet integration method applying the λ fuzzy measure. The combination grade is evaluated higher, when more combination of a command chains appear in an inspecting command sequence. The results of our experiments showed that the intrusion detection rate was 92.8%, and was fairly improved compared with the rate 70% by the former method with the probability measure. Furthermore, it turns out that in the intrusion detection, the combination of command chains has larger effect than the frequency of appearance of command chains is attestation.

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It is very difficult for a conventional PID controller to achieve good control of a small vessel under any operating conditions, because the dynamics of the vessel varies significantly with speed, weight, and disturbances such as wind, waves, tidal currents, etc. Since the autopilots, which have already been developed for large vessels, require the system identification or the reference model, they are not suitable for small vessels. The purpose of this research is to realize the adaptive autopilot for small vessels without the system identification or the reference model, which can be achieved by unsupervised learning. The adaptation needs the adequate evaluation method of the behavior of the system under control. We propose the evaluation method employing Trajectory On Phase diagram (E-TOP) as the new evaluation method for small vessels in order to build up the adaptive autopilot for them. Moreover, the new adaptive autopilot system is examined with a vessel simulator and a real pleasure boat to show the E-TOP method is much more effective rather than a conventional PID controller.

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In this paper, the interval data whose boundary of interval is vague are called as 'fuzzy interval data.' We consider the analysis of the expected utility and the amount of information using the fuzzy interval data. Here, the formulation of the fuzzy interval data using the concept of the probability of fuzzy events defined by Zadeh is performed. However, the method with direct usage of the membership functions of fuzzy interval data incurs the following problems; (i) There is a need to grasp the shapes of membership functions precisely, (ii) Treating the membership functions precisely causes the complexity of calculation. To solve these problems, we propose the method treating the middle points of membership functions as the representative values. As a result, even if fuzzy interval data are obtained, the analysis of expected utility which is not so far different from conventional expected utility is carried out. In real situations, the observers do not always obtain the symmetrical membership functions. So, we set up the asymmetrical trapezoidal membership functions and carried out the numerical examples. As a result, the usefulness of our proposed method is proved.

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