Abstract: A radiated electromagnetic wave estimation is performed by a computer. The estimation process includes: converting a circuit diagram of an electronic circuit board into a combination of a plurality of partial circuits; and predicting radiated electromagnetic waves from the electronic circuit board by using a prediction result of a radiated electromagnetic wave for each of the partial circuits obtained by the converting.

Abstract: A non-transitory computer-readable recording medium storing a training data generation program for causing a computer to perform processing including: obtaining circuit information; determining whether or not a relationship between a distance between two lines included in the circuit information and a distance between the two lines and a GND layer satisfies a condition; when the relationship satisfies the condition, generating first current distribution information associated with the two lines by simulation and generating training data for machine learning based on the first current distribution information; and when the relationship does not satisfy the condition, generating second current distribution information associated with the two lines by synthesizing pieces of current distribution information associated with the respective two lines and generating the training data for machine learning based on the second current distribution information.

Abstract: A non-transitory computer-readable storage medium storing a n EMI calculation program that causes at least one computer to execute a process, the process includes inputting circuit information of a first circuit to a machine learning model; acquiring an EMI value at a certain frequency of the first circuit; selecting, based on an impedance characteristic of the first circuit and the EMI value at the certain frequency, first EMI information from a plurality of pieces of EMI information in each of which an impedance characteristic of each of a plurality of circuits is associated with EMI values at a plurality of frequencies of each of the plurality of circuits; and acquiring an EMI value at another frequency different from the certain frequency of the first circuit based on the EMI value at the certain frequency and the first EMI information.

Abstract: A non-transitory computer-readable recording medium storing a training data generation program for causing a computer to execute processing including: calculating, for each of a first plurality of pieces of circuit information, a characteristic impedance of a circuit included in the each of the first plurality of pieces of circuit information; classifying the first plurality of pieces of circuit information based on the calculated characteristic impedance; selecting one or more of pieces of circuit information from a second plurality of pieces of circuit information, each of the second plurality of pieces of circuit information being, among the first plurality of pieces of circuit information, a piece of circuit information classified into a first group by the classifying; and generating training data for machine learning based on the selected one or more of pieces of circuit information.

Abstract: A non-transitory computer-readable storage medium storing an electromagnetic field analysis program that causes at least one computer to execute a process, the process includes specifying a dimension of a width of wiring included in first circuit information and a dimension of a thickness of the wiring; generating second circuit information obtained by changing value of one selected from the dimension of the width and the dimension of the thickness to zero based on a ratio between the dimension of the width and the dimension of the thickness; and executing an electromagnetic field analysis based on the second circuit information.

Abstract: A non-transitory computer-readable storage medium storing an equivalent circuit analysis program that causes at least one computer to execute a process, the process includes specifying a surface pattern included in first circuit information; generating second circuit information in which the surface pattern is changed to a line pattern based on a wire of a layer adjacent to the surface pattern; and executing an equivalent circuit analysis based on the second circuit information.

Abstract: An information processing apparatus calculates a value based on the lengths of wires included in inner layers selecting the inner layers other than outermost layers and layers adjacent to the outermost layers from among a plurality of layers included in circuit data. The information processing apparatus generates training data including first layer data corresponding to the patterns of the outermost layers, second layer data corresponding to the patterns of the layers adjacent to the outermost layers, and the value based on the lengths of the wires. The information processing apparatus trains a machine learning model by using the training data.

Abstract: An information processing apparatus specifies a first pattern indicating a first layer included in first circuit data. The information processing apparatus generates, based on first wiring included in a second pattern indicating a second layer that is adjacent to the first layer and a slit included in the first pattern, second circuit data by changing the first pattern to a third pattern including second wiring corresponding to the first wiring. The information processing apparatus generates, based on the second circuit data, training data for machine learning.

Abstract: An estimation method is performed by a computer for estimating a far field of electromagnetic waves or heat. The method includes: generating an emphasis pattern image obtained by emphasizing each target element of a pattern image of a target circuit by an emphasizing method that corresponds to a type of each target element, with respect to the target element which is at least a part of elements included in the target circuit; and estimating the far field of electromagnetic waves or heat radiated from the target circuit by an existing estimation model using the emphasis pattern image.

Abstract: A non-transitory computer-readable storage medium storing a n EMI calculation program that causes at least one computer to execute a process, the process includes inputting circuit information of a first circuit to a machine learning model; acquiring an EMI value at a certain frequency of the first circuit; selecting, based on an impedance characteristic of the first circuit and the EMI value at the certain frequency, first EMI information from a plurality of pieces of EMI information in each of which an impedance characteristic of each of a plurality of circuits is associated with EMI values at a plurality of frequencies of each of the plurality of circuits; and acquiring an EMI value at another frequency different from the certain frequency of the first circuit based on the EMI value at the certain frequency and the first EMI information.

Abstract: An information processing apparatus specifies a first pattern indicating a first layer included in first circuit data. The information processing apparatus generates, based on first wiring included in a second pattern indicating a second layer that is adjacent to the first layer and a slit included in the first pattern, second circuit data by changing the first pattern to a third pattern including second wiring corresponding to the first wiring. The information processing apparatus generates, based on the second circuit data, training data for machine learning.

Abstract: An information processing apparatus calculates a value based on the lengths of wires included in inner layers selecting the inner layers other than outermost layers and layers adjacent to the outermost layers from among a plurality of layers included in circuit data. The information processing apparatus generates training data including first layer data corresponding to the patterns of the outermost layers, second layer data corresponding to the patterns of the layers adjacent to the outermost layers, and the value based on the lengths of the wires. The information processing apparatus trains a machine learning model by using the training data.

Abstract: The present invention relates to a machine learning program for causing a computer to execute a process. In an example, the process executed by the computer when the program is executed includes: acquiring a current distribution image by an equivalent circuit simulation based on circuit information; acquiring a shape image that indicates a shape of a circuit based on the circuit information; acquiring an EMI value by electromagnetic field analysis based on the circuit information; and generating an EMI prediction model by machine learning based on training data that includes the current distribution image, the shape image, and the EMI value.

Abstract: A non-transitory computer-readable recording medium has stored therein a program that causes a computer to execute a process, the process including identifying, for an electronic circuit to be analyzed, a resonance frequency of a current and a spatial distribution of the current that flows through the electronic circuit to be analyzed at the resonance frequency, generating a machine learning model using a training data set in which arrangements of circuit elements in respective electronic circuits differ from each other, inputting a value of the identified resonance frequency and information of the identified spatial distribution to the generated machine learning model, and estimating an electromagnetic wave radiation situation of the electronic circuit to be analyzed, based on an output from the machine learning model according to the inputting.

Abstract: A radiated electromagnetic wave estimation is performed by a computer. The estimation process includes: converting a circuit diagram of an electronic circuit board into a combination of a plurality of partial circuits; and predicting radiated electromagnetic waves from the electronic circuit board by using a prediction result of a radiated electromagnetic wave for each of the partial circuits obtained by the converting.

Abstract: An estimation method is performed by a computer for estimating a far field of electromagnetic waves or heat. The method includes: generating an emphasis pattern image obtained by emphasizing each target element of a pattern image of a target circuit by an emphasizing method that corresponds to a type of each target element, with respect to the target element which is at least a part of elements included in the target circuit; and estimating the far field of electromagnetic waves or heat radiated from the target circuit by an existing estimation model using the emphasis pattern image.