Jump to main content

博士論文

A study of effective framework combining sparse autoencoder based feature transfer learning and long short-term memory for network intrusion detection system

Icons representing 博士論文
The cover of this title could differ from library to library. Link to Help Page

Available in National Diet Library

Find on the publisher's website

国立国会図書館デジタルコレクション

A study of effective framework combining sparse autoencoder based feature transfer learning and long short-term memory for network intrusion detection system

Persistent ID (NDL)
info:ndljp/pid/11488697
Material type
博士論文
Author
Zolzaya Kherlenchimeg
Publisher
Zolzaya Kherlenchimeg
Publication date
2020
Material Format
Digital
Capacity, size, etc.
-
Name of awarding university/degree
岩手大学,博士(工学)
View All

Notes on use at the National Diet Library

本資料は、掲載誌(URI)等のリンク先にある学位授与機関のWebサイトやCiNii DissertationsLeave the NDL website. から、本文を自由に閲覧できる場合があります。

Search by Bookstore

Search by Bookstore

Read this material in an accessible format.

View materials in accessible formats for people with print disabilities (1Type)

Search by Bookstore

Read in Disability Resources

Bibliographic Record

You can check the details of this material, its authority (keywords that refer to materials on the same subject, author's name, etc.), etc.

Digital

Material Type
博士論文
Title
A study of effective framework combining sparse autoencoder based feature transfer learning and long short-term memory for network intrusion detection system
Author/Editor
Zolzaya Kherlenchimeg
Publication, Distribution, etc.
Zolzaya Kherlenchimeg
Publication Date
2020
Publication Date (W3CDTF)
2020
Degree grantor/type
岩手大学
Date Granted
2020-03-23
Date Granted (W3CDTF)
2020-03-23
Dissertation Number
甲第317号