상세정보
Export to Refworks부가기능
Handbook of machine learning for computational optimization applications and case studies
상세 프로파일
| 자료유형 | 단행본 |
|---|---|
| 서명/저자사항 | Handbook of machine learning for computational optimization : applications and case studies/ edited by Vishal Jain, Sapna Juneja, Abhinav Juneja, and Ramani Kannan. |
| 개인저자 | Jain, Vishal,1983- editor, |
| 발행사항 | Boca Raton, FL: CRC Press, 2022. |
| 형태사항 | 1 online resource (xiv, 280 pages): illustrations (some color). |
| 총서사항 | Demystifying technologies for computational excellence : moving towards society 5.0 |
| 기타형태 저록 | Print version: Handbook of machine learning for computational optimization Boca Raton : CRC Press, 2021 9780367685423 |
| ISBN | 9781003138020 1003138020 1000455688 9781000455670 100045567X 9781000455687 |
| 기타표준부호 | 10.1201/9781003138020doi |
| 서지주기 | Includes bibliographical references and index. |
| 내용주기 | Random variables in machine learning / Dr. Piratla Srihari -- Analysis of EMG signals using extreme learning machine with nature inspired feature selection techniques / A. Anitha and Bakiya Ambikapathy -- Detection of breast cancer by using various machine learning and deep learning algorithms / Yogesh Jadhav, Harsh Mathur -- Assessing the radial efficiency performance of bus transport sector using data envelopment analysis / Swati Goyal, Shivi Agarwal, Trilok Mathur and Nirbhay Mathur. |
| 요약 | "Technology is moving at an exponential pace in this era of computational intelligence. Machine Learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new Machine Learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach which makes Machine Learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms which are more efficient and reliable for new dimensions in discovering other applications and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for Machine Learning based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers"-- |
| 해제 | Provided by publisher. |
| 일반주제명 | Machine learning --Industrial applications. Mathematical optimization --Data processing. Artificial intelligence. TECHNOLOGY / Operations Research Artificial intelligence. Machine learning --Industrial applications. Mathematical optimization --Data processing. |
| 언어 | 영어 |
| 바로가기 |  |
