Kabushiki Kaisha Toshiba

Tadayoshi Murayama

Akira Sawada

Kenji Adachi

Keiichi Sasaki

Shuichiro Kobayashi

Kazushige Kimura

Katsumi Kanehira

Yoko Todo

Masaaki Ookubo

Hiromi Imai

Fuktoshi Kurokawa

In a method of degradation diagnosis according to the present invention, an equipment degradation diagnosis request is input through network from a diagnosis requester and a degradation diagnosis requests handler is selected in accordance with execution condition information of degradation diagnosis specified in respect of at least one degradation diagnosis requests handler and condition information in accordance with which an diagnosis requester requests degradation diagnosis. A request for execution of degradation diagnosis is made to this selected degradation diagnosis requests handler and the results of execution of the degradation diagnosis obtained by the selected degradation diagnosis requests handler are acquired and output through network to the diagnosis requester. In this way, a service can be implemented whereby diagnosis of degradation requested by a diagnosis requester from a diagnostic service provider is performed rapidly and easily at low cost.

Degradation diagnostic method, degradation diagnostic mediation device and degradation diagnostic device and computer-readable recording medium on which a program is recorded

The distributed water flow predicting device comprises seasonal prediction model learning means for learning weight coefficients by back propagation over a prediction model a neural network model for predicting daily distributed water flows and specific characters of an hourly distributed water flow pattern for a season, based on processed actual seasonal weather data and seasonal distributed water flows, so as to identify the prediction model. Seasonal distributed water flow predicting means pridicts daily distributed water flows and specific characters of hourly distributed water flow patterns for a required season by using the prediction model, based on inputted information about the weather, temperature, a weekday or a holiday. The seasonal distributed water flow predicting means compares the specific characters of an hourly distributed water flow pattern given by the prediction model with specific characters of past actual distributed water flow patterns so as to retrieve a most similar hourly distributed flow pattern from the past actual distributed water flow patterns, giving the retrieved pattern as a predicted hourly distributed water flow pattern, and multiplys the predicted daily distributed water flow by the predicted hourly distributed water flow pattern to predict an hourly distributed water flow.

Distributed water flow predicting device

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Chiba-ken, Japan

Tadayoshi Murayama