Patent Document ID: 7966280
Application ID: 12069579

Base Claim:
1. An automotive air conditioner comprising: an air-conditioning unit for supplying conditioned air into a vehicle; an information acquiring unit for acquiring state information indicating a state related to said vehicle; a storage unit for storing a plurality of pieces of said state information as respective learned data; a learning unit, by using said learned data, for constructing a probabilistic model into which said state information is entered in order to calculate the probability of a vehicle occupant performing a specific setting operation; a control information correcting unit for calculating said probability by entering said state information into the probabilistic model constructed by said learning unit, and for correcting setting information or control information related to the setting operation of said occupant in accordance with said calculated probability so as to achieve said specific setting operation; and an air-conditioning control unit for controlling said air-conditioning unit in accordance with said corrected setting information or control information, wherein said learning unit comprises: a clustering subunit for classifying said plurality of learned data stored in said storage unit into at least a first cluster and a second cluster, and for determining a first range for a value of said state information from the learned data included in said first cluster and a second range for the value of said state information from the learned data included in said second cluster; and a probabilistic model constructing subunit for constructing said probabilistic model associated with said specific setting operation by determining the probability of occurrence of the value of said state information contained in said first range and the probability of occurrence of the value of said state information contained in said second range.

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Claim 7:
7. The automotive air conditioner according to claim 1 , wherein said probabilistic model has a group of nodes consisting of a node that takes said state information as an input and that outputs a conditional probability of a specific event and at least one other node that takes the output of said node as an input and that outputs the probability of said occupant performing said specific setting operation, and said node has a conditional probability table that indicates said conditional probability for the case where the value of said state information is contained in said first range as well as for the case where the value of said state information is contained in said second range, and said probabilistic model constructing subunit obtains from said plurality of learned data the number of times that said specific even has occurred for the case where the value of said state information is contained in said first range as well as for the case where the value of said state information is contained in said second range, creates said conditional probability table by dividing said number of times by the total number of said plurality of learned data and thereby obtaining said conditional probability for the case where the value of said state information is contained in said first range as well as for the case where the value of said state information is contained in said second range, and stores said conditional probability table in said storage unit by associating said conditional probability table with said node.