This paper presents a method which achieves an optimal order planning using a combinatorial acution which is an autonomous distributed technique. In many actual situation, each company which constitutes the supply chain cannot disclose confidential information to other companies. Especially this study focuses sharing information kept by the alliance companies. Numerical experiments are performed for evaluating the effectiveness of the proposed method.
Rough Sets theory is widely used as a method for estimating and/or inducing the knowledge structure of if-then rules from a decision table after a reduct of the table. The concept of a reduct is that of constructing a decision table by necessary and sufficient condition attributes to induce the rules. This paper retests the reduct by the conventional methods by the use of simulation datasets after summarizing the reduct briefly and points out several problems of their methods. Then a new reduct method based on a statistical viewpoint is proposed. The validity and usefulness of the method is confirmed by applying it to the simulation datasets and “Car Evaluation Database ” in UCI (University of California, Irvine) dataset. Particularly, this paper shows a statistical local reduct method, very useful for estimating if-then rules hidden behind the decision table of interest.
We proposed a new color transfer method using a gradation plate which we defined as features obtained from the color distribution of images before. The method involves such process as moving the gradation plate of a target image close to the gradation plate of the referred image which has the intended tones. Then recognizing that, it is a subject to evaluate the results objectively. To that end, we conduct the sensibility evaluation experiments of this color transfer method, and here we report the results. By this experiment, we show one case that the impression of an object image is suitably close to the impression of a referred image and another case that transferring is not done effectively. We discuss the ways to improve the latter case.
In this paper, we find a large-scale interconnected dynamical system that reinforces its own dissipation performance via scale-expansion. First, a special class of dissipative systems is defined, which reinforces the dissipation performance via negative feedback connection. Then, the dissipativity reinforcement analysis is further extended to that for large-scale interconnected systems. We find two interconnection rules on which the interconnected system gradually reinforces the performance via the increase of the number of subsystems.
We describe a tractable numerical procedure using polynomial kernel functions to prove the nonexistence of Lyapunov functions. The algorithm terminates in polynomial time of the dimension of the state space, the number of sample states, the degree of the polynomials appear in the system,and the degree of the Lyapunov candidate polynomial functions. The algorithm is also avairable to construct Lyapunov functions with SOS techniques. We demonstrate the appearance by some simple numerical examples.