Abstract: An information processing apparatus comprising processing circuitry, the processing circuitry constructs a prediction model for predicting time-series data related to a state of a device/equipment, calculates a prediction error that is a difference between a predicted value of the time-series data predicted by the prediction model and an actual value of the time-series data, divides the prediction error into a plurality of first sections in a time axis direction, calculates a state change amount of the actual value based on the prediction error divided into the plurality of first sections; and constructs a state determination model for determining the state of the device/equipment based on the state change amount.

Abstract: An information processing device according to an embodiment estimates a probability distribution of a maximum value or a minimum value of time-series target sensor data in a designated estimation period after a base time. The information processing device includes one or more hardware processors that: calculate a reference feature amount representing a feature of related sensor data at a reference time before the base time based on a preset feature amount calculation model; estimate a reference distribution parameter in a reference period based on a preset parameter estimation model; update the feature amount calculation model and the parameter estimation model; calculate an estimation feature amount representing the feature of related sensor data at the base time based on the updated feature amount calculation model; and estimate an estimation distribution parameter based on the updated parameter estimation model.

Abstract: An information processing device according to an embodiment estimates a probability distribution of a maximum value or a minimum value of time-series target sensor data in a designated estimation period after a base time. The information processing device includes one or more hardware processors that: calculate a reference feature amount representing a feature of related sensor data at a reference time before the base time based on a preset feature amount calculation model; estimate a reference distribution parameter in a reference period based on a preset parameter estimation model; update the feature amount calculation model and the parameter estimation model; calculate an estimation feature amount representing the feature of related sensor data at the base time based on the updated feature amount calculation model; and estimate an estimation distribution parameter based on the updated parameter estimation model.

Abstract: An information processing device includes a memory and one or more processors coupled to the memory. The one or more processors are configured to: generate a plurality of segments segmented by respective operating states of a target device based on time-series sensor data detected by a sensor that observes the target device; extract target data included in a segment having the same operating state as the operating state at certain first time out of the segments; and generate estimated data estimated to be output from the sensor at specified time different from the first time based on the target data.