Nec Corporation

Wemer Wee

Yoshio Kameda

Riki Eto

Yusuke Kikuchi

Itaru Nishioka

Yasuhisa Suzuki

A change in a weighting coefficient for an explanatory variable in an objective function used to optimize a target is received, and the target is optimized based on the objective function to which the changed weighting coefficient has been applied.

Optimization device, optimization method, and recording medium

A control customization systemcustomizes a plant control. A profilerpredicts actions of a user depending on situations of the plant or the user. A plannerdetermines an appropriate set of objectives which represent tasks desired by the user, and objective terms representing elements for controlling the plant so as to realize the objectives, and tunes the objective terms based on predictions of the profiler

Control customization system, control customization method, and control customization program

An expert model unitgenerates predicted expert control actions based on an expert model which is a machine learning model trained using data collected when an expert operated a plant which is a control target or a plant of the same or similar characteristics. A transformerconstructs metrics or error measures involving the predicted expert control actions from the expert model unitas an objective term. A combinercollects different objective terms from the transformerand a learner which outputs machine-learning models as objective terms and computes an optimal set of weights or combinations of the objective terms to construct an aggregated cost function for use in an optimizer.

Control objective integration system, control objective integration method and control objective integration program

A vehicle control system for controlling driving of a vehicle reflecting an environment and a characteristic of a user, while suppressing increase in learning time, is provided. The vehicle control system includes classification means for classifying, by using one or more attributes selected from accumulation means for accumulating data including attributes relating to driving of a vehicle, driving properties included in the data, learning means for learning a model representing the driving property, for each of types that are a result of classification by the classification means, and control information determination means for determining, by using the model learned for the type associated with a value of the attribute at time of driving of a control target vehicle, control information for the driving.

Vehicle control system, vehicle control method, and program recording medium

A toll control apparatusincludes a traffic volume prediction unitthat predicts a future overall traffic volume on a first roadand a second road, a toll control unitthat outputs, with the predicted overall traffic volume and a predetermined road toll as inputs, a future traffic volume and a predicted traveling speed on the second road for a case where a toll on the second road is set to the predetermined road toll, and a toll optimization unit. The toll optimization unitsets one or more road toll candidates, selects a road toll candidate for which the predicted traveling speed obtained by inputting the road toll candidate to the toll control unitis greater than or equal to a threshold value, and sets the road toll candidate that maximizes the toll revenue for the second road among the selected road toll candidates.

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Tokyo, Japan

Wemer Wee