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工業人工智能概論 版權信息
- ISBN：9787121381621
- 條形碼：9787121381621 ; 978-7-121-38162-1
- 裝幀：平裝-膠訂
- 冊數：暫無
- 重量：暫無
- 所屬分類：>>
工業人工智能概論 本書特色
本書以人工智能技術在工業中的應用為出發點，系統、深入地闡述了工業人工智能的關鍵技術，并給出了大量的應用案例。全書共 5 章，包括緒論、數據分析與數據挖掘工具、機器學習、深度學習和工業人工智能面臨的挑戰。本書可作為相關專業的本科生及研究生學習工業人工智能的入門教材，也可作為專業技術人員了解工業人工智能的培訓教材和參考書，還可作為對工業人工智能感興趣的各界人士的普及性讀物。
工業人工智能概論 內容簡介
本書共分五章, 系統介紹了工業人工智能的內涵和發展, 詳細分析了工業人工智能關鍵技術, 從實際應用出發, 重點闡述了工業人工智能數據分析工具、機器學習基礎和深度學習方法, 結合工業應用需求, 給出了大量應用案例。
工業人工智能概論 目錄
第 1 章 緒論·····················································································1
1.1 人工智能的內涵及發展····································································1
1.2 工業人工智能的內涵及發展······························································4
1.2.1 工業人工智能的發展背景 ·····························································4
1.2.2 工業人工智能的發展歷程 ·····························································6
1.2.3 工業人工智能與傳統人工智能的區別················································7
1.3 工業人工智能的算法功能和典型應用··················································8
1.4 工業人工智能的知識體系································································11
1.5 工業人工智能的關鍵技術································································12
第 2 章 數據分析與數據挖掘工具··························································14
2.1 工業大數據的特點··········································································15
2.2 工業大數據挖掘的定義及過程···························································17
2.3 工業數據的特征分析·······································································18
2.3.1 工業數據的統計描述 ···································································18
2.3.2 工業數據的相關性分析 ································································20
2.4 工業數據的預處理··········································································23
2.4.1 異常值處理 ···············································································23
工業數據異常值的處理案例 ·····························································25
2.4.2 缺失值處理 ···············································································26
工業數據缺失值的處理案例 ·····························································27
2.4.3 數據歸一化處理 ·········································································28
2.4.4 不等時距數據處理 ······································································28
工業數據不等時距處理案例·····························································.29
2.4.5 離群點檢測···············································································.32
2.4.6 不平衡數據集檢測······································································.34
2.4.7 數據降維處理············································································.36
2.5 假設檢驗····················································································.41
2.5.1 假設檢驗的基本原理···································································.41
2.5.2 假設檢驗的一般步驟···································································.42
2.5.3 假設檢驗的種類·········································································.42
2.6 多變量分析模型 ··········································································.44
2.6.1 線性模型··················································································.44
2.6.2 廣義線性模型············································································.45
2.6.3 線性混合效應模型······································································.47
2.7 *大似然估計··············································································.48
2.8 關聯分析····················································································.49
2.8.1 關聯規則挖掘···········································································.·51
2.8.2 關聯規則算法···········································································.·52
2.8.3 時序關聯規則算法······································································.54
2.8.4 一維時序關聯規則······································································.56
2.8.5 多維時序關聯規則······················································.··············.59
2.9 數據分析系統的體系架構 ··············································.··············.64
第 3 章 機器學習 ····························································.···············.65
3.1 人類的思考過程與機器學習的過程 ···················································.65
3.2 機器學習的知識體系 ···················································.················.67
3.3 Python 語言的優勢·········································································.68
3.4 工業人工智能的有監督學習算法 ·······················································.68
3.4.1 決策樹算法···············
1.1 人工智能的內涵及發展····································································1
1.2 工業人工智能的內涵及發展······························································4
1.2.1 工業人工智能的發展背景 ·····························································4
1.2.2 工業人工智能的發展歷程 ·····························································6
1.2.3 工業人工智能與傳統人工智能的區別················································7
1.3 工業人工智能的算法功能和典型應用··················································8
1.4 工業人工智能的知識體系································································11
1.5 工業人工智能的關鍵技術································································12
第 2 章 數據分析與數據挖掘工具··························································14
2.1 工業大數據的特點··········································································15
2.2 工業大數據挖掘的定義及過程···························································17
2.3 工業數據的特征分析·······································································18
2.3.1 工業數據的統計描述 ···································································18
2.3.2 工業數據的相關性分析 ································································20
2.4 工業數據的預處理··········································································23
2.4.1 異常值處理 ···············································································23
工業數據異常值的處理案例 ·····························································25
2.4.2 缺失值處理 ···············································································26
工業數據缺失值的處理案例 ·····························································27
2.4.3 數據歸一化處理 ·········································································28
2.4.4 不等時距數據處理 ······································································28
工業數據不等時距處理案例·····························································.29
2.4.5 離群點檢測···············································································.32
2.4.6 不平衡數據集檢測······································································.34
2.4.7 數據降維處理············································································.36
2.5 假設檢驗····················································································.41
2.5.1 假設檢驗的基本原理···································································.41
2.5.2 假設檢驗的一般步驟···································································.42
2.5.3 假設檢驗的種類·········································································.42
2.6 多變量分析模型 ··········································································.44
2.6.1 線性模型··················································································.44
2.6.2 廣義線性模型············································································.45
2.6.3 線性混合效應模型······································································.47
2.7 *大似然估計··············································································.48
2.8 關聯分析····················································································.49
2.8.1 關聯規則挖掘···········································································.·51
2.8.2 關聯規則算法···········································································.·52
2.8.3 時序關聯規則算法······································································.54
2.8.4 一維時序關聯規則······································································.56
2.8.5 多維時序關聯規則······················································.··············.59
2.9 數據分析系統的體系架構 ··············································.··············.64
第 3 章 機器學習 ····························································.···············.65
3.1 人類的思考過程與機器學習的過程 ···················································.65
3.2 機器學習的知識體系 ···················································.················.67
3.3 Python 語言的優勢·········································································.68
3.4 工業人工智能的有監督學習算法 ·······················································.68
3.4.1 決策樹算法···············
展開全部
工業人工智能概論 作者簡介
2008.03-2010.12：東北大學秦皇島分校講師；2011.01-2016.12：東北大學秦皇島分校副教授；2017.01-至今：東北大學秦皇島分校教授；2012年榮獲秦皇島市十大青年風尚人物稱號；2013年度河北省"三三三人才工程”第三層次人選；2014年榮獲秦皇島市優秀科技工作者稱號
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