Abstract: In a method of degradation diagnosis according to the present invention, an equipment degradation diagnosis request is input through network 4 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 4 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.

Abstract: In a method of degradation diagnosis according to the present invention, an equipment degradation diagnosis request is input through network 4 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 4 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.

Abstract: 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.