A bias estimation apparatus according to an embodiment estimates a bias included in a measured values by each sensor. The bias estimation apparatus includes a reference model builder, a temporary bias generator, a corrected measured value calculator, a similarity calculator, a similarity selector, a score calculator, and an estimated bias determiner. The reference model builder builds a reference model of the measured value packs. The temporary bias generator generates a temporary bias pack. The corrected measured value calculator calculates corrected measured value packs. The similarity calculator calculates a similarity of each corrected measured value pack. The similarity selector selects a part of the similarities according to their values from among the similarities. The score calculator calculates a score based on the selected similarities. The estimated bias determiner determines an estimated bias which is an estimated value of the bias based on the score.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A bias estimation apparatus for estimating a bias included in a measured values by each sensor, comprising: a reference model builder configured to build a reference model of the measured value packs each of which is measured values by sensors in a single measurement action; a temporary bias generator configured to generate a temporary bias pack which is temporary estimated values of the biases of sensors; a corrected measured value calculator configured to calculate corrected measured value packs each of which is the measured value pack corrected by the temporary bias pack; a similarity calculator configured to calculate a similarity of each corrected measured value pack relative to the reference model; a similarity selector configured to select a part of the similarities according to their values from among the similarities calculated by the similarity calculator; a score calculator configured to calculate a score which indicates a similarity of the whole corrected measured value packs relative to the reference model based on the selected similarities; and an estimated bias determiner configured to determine an estimated bias which is an estimated value of the bias for each sensor based on the score. 2. The apparatus according to claim 1, wherein the similarity selector selects the similarities in an order from the largest value. 3. The apparatus according to claim 1, wherein the score calculator calculates any one of an average value, a median, and a mode of the selected similarities as the score. 4. The apparatus according to claim 1, wherein the temporary bias generator generates the plurality of temporary bias packs, and the estimated bias determiner determines the temporary bias pack with the maximum score as the estimated bias pack of which each element is the estimated bias of a sensor from among the plurality of temporary bias packs. 5. The apparatus according to claim 1, wherein the reference model builder builds the reference model by using principal component analysis. 6. The apparatus according to claim 1, wherein the reference model builder builds the reference model by using a neural network. 7. The apparatus according to claim 1, wherein the similarity selector selects the similarity with the value which is the maximum value and the similarity with the value which is the median. 8. The apparatus according to claim 7, wherein the score calculator calculates a difference of square roots of the selected similarities as the score. 9. The apparatus according to claim 1, further comprising: a data converter configured to convert qualitative variables into quantitative variables, wherein the measured value packs include the quantitative variables converted from the qualitative variables by the data converter. 10. A bias estimation method for estimating a bias included in measured values by each sensor, comprising: building a reference model of the measured value packs each of which is measured values by sensors in a single measurement action; generating a temporary bias pack which is temporary estimated values of the biases of sensors; calculating corrected measured value packs each of which is the measured value pack corrected by the temporary bias pack; calculating a similarity of each corrected measured value pack relative to the reference model; selecting a part of the similarities according to their values from among the similarities calculated by the similarity calculator; calculating a score which indicates a similarity of the whole corrected measured value packs relative to the reference model based on the selected similarities; and determining an estimated bias which is an estimated value of the bias for each sensor based on the score. 11. The method according to claim 10, wherein the similarities are selected in an order from the largest value in selecting the similarities. 12. The method according to claim 10, further comprising: converting qualitative variables into quantitative variables, wherein the measured value packs include the quantitative variables converted from the qualitative variables. 13. A failure diagnosis apparatus for diagnosing failures of sensors, comprising: the apparatus according to claim 1; and a score calculator configured to calculate a score which indicates a similarity of the whole corrected measured value packs relative to the reference model based on the selected similarities; and a failure diagnoser configured to diagnose failures of sensors based on the score. 14. The apparatus according to claim 13, further comprising: a temporary bias generator configured to generate a temporary bias pack which is temporary estimated values of the biases of sensors; and a corrected measured value calculator configured to calculate corrected measured value packs each of which is the measured value pack corrected by the temporary bias pack, wherein the similarity calculator calculates a similarity of each corrected measured value pack relative to the reference model, the similarity selector selects a part of the similarities according to their values from among the similarities calculated by the similarity calculator, the score calculator calculates a score which indicates a similarity of the whole corrected measured value packs relative to the reference model based on the selected similarities, the estimated bias determiner determines an estimated bias which is an estimated value of the bias for each sensor based on the score, and the failure diagnoser diagnoses failures of the sensors based on the estimated biases. 15. A failure diagnosis method for diagnosing failures of the sensors, comprising: the method according to claim 10; and diagnosing failures of the sensors based on the score. 16. The method according to claim 15, further comprising: generating a temporary bias pack which is temporary estimated values of the biases of sensors; and calculating corrected measured value packs each of which is the measured value pack corrected by the temporary bias pack, wherein a similarity of each corrected measured value pack relative to the reference model is calculated, a part of the calculated similarities are selected according to their values, a score which indicates a similarity of the whole corrected measured value packs relative to the reference model is calculated based on the selected similarities, an estimated bias which is an estimated value of the bias is determined for each sensor based on the score, and failures of the sensors are diagnosed based on the estimated biases.