Elevator control apparatus

Claim 2

An elevator control apparatus for estimating car crowdedness and for controlling operation of the car using the estimated car crowdedness, comprising: an input data conversion means for converting a traffic data signal, including car position data, car direction data, car load data and data regarding car calls and hall calls into a form which is usable as an input for a neural net; an estimated car crowdedness unit including a neural net having an input layer for receiving neural net data from said input data conversion means, an output layer for outputting a signal representative of the estimated car crowdedness of a selected car, and an intermediate layer provided between the input an output layers in which weighting factors are set; an output data conversion means for converting the signal output from the output layer into an operational control data signal; a learning data creation means including a memory unit for storing both the estimated car crowdedness for a predetermined hall and the input data at a predetermined time, for storing, as actual car crowdedness, the car crowdedness when said car stops at or passes the predetermined hall, and for outputting the stored input data, the estimated car crowdedness and the actual car crowdedness as one learning data pair signal; and a correction means for correcting the weighting factors set in the intermediate layer of the estimated car crowdedness unit using the learning data signal said correction means being connected to said learning data creation means and to said estimated car crowdedness unit.

Claim 3

An elevator control apparatus according to claim 1 wherein the input, intermediate and output layers in said estimated car crowdedness unit each have a plurality of nodes, the intermediate layer containing weighting factors between the individual nodes of the input layer and the individual nodes of the intermediate layer and weighting factors between the individual nodes of the intermediate layer and the individual nodes of the output layer.

Claim 4

An elevator control apparatus according to claim 1 wherein said input data conversion means has a standardization means for standardizing the traffic data into a value ranging from 0 to 1.

Claim 5

An elevator control apparatus according to claim 1 wherein said estimated car crowdedness unit determines the estimated car crowdedness each time a hall call is registered.

Claim 6

An elevator control apparatus according to claim 1 wherein said learning data creation means repeatedly creates the learning data at predetermined intervals of time.

Claim 7

An elevator control apparatus according to claim 1 wherein said learning data creation means repeatedly creates the learning data each time any of previously determined typical statuses of the car is detected.

Claim 8

An elevator control apparatus according to claim 1 wherein said learning data creation means repeatedly creates the learning data each time allocation of the hall call is made.

Claim 9

An elevator control apparatus according to claim 1 wherein said estimated car crowdedness unit uses an estimated value of the car load as the estimated car crowdedness.

Claim 10

An elevator control apparatus according to claim 1 wherein said estimated car crowdedness unit uses the probability that a car is loaded to full capacity as the estimated car crowdedness.

Claim 11

An elevator control apparatus according to claim 9 wherein said learning data creation means creates the learning data assuming that the car does not stop at a given floor when no car call is made relative in the car positioned at given floor and when the car load is above a predetermined value.

Claim 12

An elevator control apparatus according to claim 2 wherein said correction means includes means for determined a desired crowdedness from the actual crowdedness and the input data, and a means for correcting the weighting factors such that and error between the desired crowdedness and the estimated car crowdedness is reduced.

Claim 13

An elevator control apparatus according to claim 2 wherein said input data conversion means converts traffic data including statistic features of the traffic and outputs the converted traffic data to said estimated car crowdedness unit.

Claim 14

An elevator control apparatus according to claim 2 wherein said input data conversion means converts the traffic data and outputs the converted traffic data to said estimated car crowdedness operation unit.

Claim 15

An elevator control apparatus according to claim 2 wherein said correction means corrects the weighting factors repeatedly at a predetermined interval of time.

Claim 16

An elevator control apparatus according to claim 2 wherein said correction means corrects the weighting factors repeatedly each time any of previously determined typical statuses of the car is detected.

Claim 17

An elevator control apparatus according to claim 2 wherein said correction means corrects the weighting factors when the frequency with which said estimated car crowdedness unit determines operates the estimated car crowdedness is reduced.

Claim 18

An elevator control apparatus according to claim 2 wherein said estimated car crowdedness unit determines an estimated car crowdedness when a new hall call is virtually allocated to the car and when a new hall call is not virtually allocated to the car.

Claim 19

An elevator control apparatus according to claim 12 wherein said input data conversion means converts the statistical number of passengers who get on the car for a given time period and the statistical number of passengers who get off the car for a given time period and outputs them to said estimated car crowdedness operation unit.

Claim 22

An elevator control apparatus for estimating car crowdedness and for controlling operation of the car using the estimated car crowdedness, comprising: an elevator group control device which generates traffic data signals including car position data, car direction data, car load data and data regarding car calls and hall calls; an input data conversion means for converting the traffic data signals generated by said elevator group control device into a form which is usable as an input for a neural net; an estimated car crowdedness unit including a neural net having an input layer for receiving neural net data from said input data conversion means, an output layer for outputting a signal representative of the estimated car crowdedness of a selected car, and an intermediate layer provided between the input an output layers in which weighting factors are set; an output data conversion means for converting the signal output from the output layer into an operational control data signal; a learning data creation means including a memory unit for storing both the estimated car crowdedness for a predetermined hall and the input data at a predetermined time, for storing, as actual car crowdedness, the car crowdedness when said car stops at or passes the predetermined hall, and for outputting the stored input data, the estimated car crowdedness and the actual car crowdedness as a single learning data pair signal; and a correction means for correcting the weighting factors set in the intermediate layer of the estimated car crowdedness unit using the learning data signal.

Claim 23

An elevator control apparatus for estimating car crowdedness and for controlling operation of the car using the estimated car crowdedness, comprising: an elevator group control device which generates traffic data signals including car position data, car direction data, car load data and data regarding car calls and hall calls; an input data conversion means for converting the traffic data signals generated by said elevator group control device into a form which is usable as an input for a neural net; an estimated car crowdedness unit including a neural net having an input layer for receiving neural net data from said input data conversion means, an output layer for outputting a signal representative of the estimated car crowdedness of a selected car, and an intermediate layer provided between the input an output layers in which weighting factors are set; an output data conversion means for converting the signal output from the output layer into an operational control data signal; a learning data creation means including a memory unit for storing both the estimated car crowdedness for a predetermined hall and the input data at a predetermined time, for storing, as actual car crowdedness, the car crowdedness when said car stops at or passes the predetermined hall, and for outputting the stored input data, the estimated car crowdedness and the actual car crowdedness as a single learning data pair signal; and a correction means for correcting the weighting factors set in the intermediate layer of the estimated car crowdedness unit using the learning data signal.