Fujitsu Corporation

Toshiyasu Ohara

Shohei Yamane

Yoichi Kochibe

Takashi Yamazaki

Hiroaki Yamada

Takanori Negishi

Kazuya Yamaura

Yasuhiro Kawashima

Masao Fukushima

Tsuyoshi Tamaki

Toshio Arai

Masatoshi Ogawa

Hiroaki Watanabe

Yusuke Oishi

Takashi Kobayashi

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.

Computer-readable recording medium storing machine learning program, information processing apparatus, and machine learning method

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.

Program storage medium, method, and information processing device for radiated electromagnetic wave estimation

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.

Machine learning method and computing system

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.

Training data generating method and computing system

A structural analysis method executed by a computer, includes acquiring model information; evaluating based on the acquired model information, a degree of agglomeration of a model subject to analysis; and selecting for the model, a direct method or an iterative method as an algorithm to solve simultaneous linear equations of a structural analysis solver that uses a finite element method, the direct method or the iterative method being selected based on a result of evaluation of the degree of agglomeration of the model.

Structural analysis method and structural analysis apparatus

A structure analysis device includes a memory and a processor configured to obtain model information, evaluate a size of a model in accordance with the model information, select, in accordance with the evaluated size, either a direct method or an iterative method as a first algorithm of a simultaneous linear equation of a structure analysis solver that uses a finite element method, and execute structure analysis of the model by using the first algorithm.

Growing community of inventors

Nakano, Japan

Toshiyasu Ohara