Nakaji Honda

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The ink drop spread (IDS) method is a modeling technique developed by algorithmically mimicking the information-handling processes of the human brain. This method is a new paradigm of soft computing. The structure of IDS models is similar to that of artificial neural networks: they comprise distributed processing units. The beneficial property of fault(More)
In this simulation platform, signal controllers that operate in the traffic simulator show signal aspects instructed actual traffic signal controller. Because the interface of a practical signal controller transmits contact-point conditions, the interface cannot exchange information directly with a traffic simulator program operated on a personal computer.(More)
The ink drop spread (IDS) method is a modeling technique that has several advantages in real-time capabilities, tractability, and interpretability of models; thus, it has a good potential to be a useful soft computing tool. This paper presents an inferential process of the IDS method in order to deal with more than two input variables and the accuracy of(More)
Absfracl-This paper presents a hardware unit for modeling systems using the Active Learning Method (ALM). The ALM, a new methodology of soft computing, has processing units called IDS’s, which are tasked with extracting useful information from a system subject to modeling. In realizing the ALM in hardware, it is desirable in terms of processing nature,(More)