ESTIMATION OF CATALYTIC PERFORMANCE BY USING NEURAL NETWORKS

使用神经网络估计催化性能

• 批准号: 10650776
• 负责人: KITO Shigeharu
• 金额: $ 2.18万
• 依托单位: AICHI INSTITUTE OF TECHNOLOGY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1998
• 资助国家: 日本
• 起止时间: 1998 至 1999
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10650776/
• 关键词: neural network; catalytic performance; training data; back propagation; function overshooting; 触媒性能予測; RBF; 正規分布関数

In this investigation, the methods of promoting estimation reliability of neural network for the case of catalytic performance are experimentally discussed from the information science viewpoints. The problem of function value overshooting encountered in the process of learning with error back-propagation neural networks is computationally investigated for the specific case of two-variable nonlinear functions. The experimental results suggests that the allowance of as large as magnitude of calculated function values should be reserved between those values and the outputs from output-layer units in order to make that learning as complete as possible. It is also concluded that the difference in application manners of training data to input layer is not critical for learning performance of those neural networks.

本文从信息科学的观点出发，对提高神经网络在催化性能预测中的可靠性进行了实验研究。针对二元非线性函数的特殊情况，研究了误差反向传播神经网络在学习过程中所遇到的函数值超调问题。实验结果表明，为了使学习尽可能完整，在这些值和输出层单元的输出之间应该保留与计算函数值大小一样大的余量。同时得出结论，训练数据应用于输入层的方式的差异对这些神经网络的学习性能并不重要。

项目成果

T. Kurokawa: "Maze-tracing algolithms applied to eye fundus blood vessels" Electronics Letters. 34. 976-977 (1998)

T. Kurokawa：“应用于眼底血管的迷宫追踪算法”《电子快报》。

S.Kito, T.Hattori: "Estimation of Catalytic Deactivation By Using Neural Networks"Theoretical Consideration of Catalytic Deactivation. in Japanese. 76-87 (1998)

S.Kito、T.Hattori：“使用神经网络估计催化失活”催化失活的理论思考。

鬼頭繁治: "ニューラルネットワークによる触媒活性劣化の予測" 1998年度触媒開発工学特別研究会報告書. 12月. 77-86 (1998)

Shigeharu Kito：“使用神经网络预测催化剂活性恶化”1998 年催化剂开发工程特别研究组报告（1998 年）。

鬼頭繁治: "ニューラルネットワークによる触媒活性劣化の研究"触媒活性劣化の学理. 76-86 (1998)

Shigeharu Kito：“使用神经网络研究催化剂活性恶化”催化剂活性恶化原理76-86（1998）。