國立虎尾科技大學 |

Recent advances in artificial intelligence in cost estimation in project management

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Recent advances in artificial intelligence in cost estimation in project management/ by Nevena Rankovic ... [et al.].
other author:	Rankovic, Nevena.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xi, 417 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Software engineering - Management -
Online resource:	https://doi.org/10.1007/978-3-031-76572-8
ISBN:	9783031765728

Recent advances in artificial intelligence in cost estimation in project management
Recent advances in artificial intelligence in cost estimation in project management[electronic resource] /by Nevena Rankovic ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xi, 417 p. :ill., digital ;24 cm. - Artificial intelligence-enhanced software and systems engineering,v. 62731-6033 ;. - Artificial intelligence-enhanced software and systems engineering ;v. 6..

Introduction -- Top AI Techniques for Every Phase of Software Project Management -- Use of AI Methods in Software Project Scheduling -- AI in Software Effort Estimation -- AI in Risk Management -- AI in Project Resource Management -- AI software project management tools -- Conclusion -- Optimizing Effort and Cost Estimation: Model Implementation using Artificial Neural Networks and Taguchi's Orthogonal Vector Plans.

This book focuses on the practical application of AI tools and techniques in software project management, offering detailed theoretical explanations and practical examples of over 40 state-of-the-art machine learning and deep learning algorithms applied across each project phase, as well as in risk and resource management. Helping the business world estimate projects more accurately while saving costs and resources is crucial in today's rapidly changing, fast-paced technological landscape. Moreover, it presents specific aspects of combined approaches through ensemble models, incorporating Taguchi's optimization method to further improve estimation accuracy, advancing this area of software project management. A valuable resource for students and professionals to deepen their knowledge and skills, it also serves as a great manual for companies adopting smarter strategies to manage and develop projects more efficiently and effectively.

ISBN: 9783031765728

Standard No.: 10.1007/978-3-031-76572-8doiSubjects--Topical Terms:

1481372
Software engineering
--Management

LC Class. No.: QA76.758 / .R36 2024

Dewey Class. No.: 005.1068

Recent advances in artificial intelligence in cost estimation in project management
LDR:02507nam a2200337 a 4500 001 1153782
003 DE-He213
005 20241206115242.0
006 m d
007 cr nn 008maaau
008 250619s2024 sz s 0 eng d
020 $a 9783031765728 $q (electronic bk.)
020 $a 9783031765711 $q (paper)
024 7 $a 10.1007/978-3-031-76572-8 $2 doi
035 $a 978-3-031-76572-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.758 $b .R36 2024
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 005.1068 $2 23
090 $a QA76.758 $b .R295 2024
245 0 0 $a Recent advances in artificial intelligence in cost estimation in project management $h [electronic resource] / $c by Nevena Rankovic ... [et al.].
260 $a Cham : $c 2024. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xi, 417 p. : $b ill., digital ; $c 24 cm.
490 1 $a Artificial intelligence-enhanced software and systems engineering, $x 2731-6033 ; $v v. 6
505 0 $a Introduction -- Top AI Techniques for Every Phase of Software Project Management -- Use of AI Methods in Software Project Scheduling -- AI in Software Effort Estimation -- AI in Risk Management -- AI in Project Resource Management -- AI software project management tools -- Conclusion -- Optimizing Effort and Cost Estimation: Model Implementation using Artificial Neural Networks and Taguchi's Orthogonal Vector Plans.
520 $a This book focuses on the practical application of AI tools and techniques in software project management, offering detailed theoretical explanations and practical examples of over 40 state-of-the-art machine learning and deep learning algorithms applied across each project phase, as well as in risk and resource management. Helping the business world estimate projects more accurately while saving costs and resources is crucial in today's rapidly changing, fast-paced technological landscape. Moreover, it presents specific aspects of combined approaches through ensemble models, incorporating Taguchi's optimization method to further improve estimation accuracy, advancing this area of software project management. A valuable resource for students and professionals to deepen their knowledge and skills, it also serves as a great manual for companies adopting smarter strategies to manage and develop projects more efficiently and effectively.
650 0 $a Software engineering $x Management $x Data processing. $3 1481372
650 0 $a Computer software $x Development $x Management. $3 657710
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Project Management. $3 787187
700 1 $a Rankovic, Nevena. $3 1481370
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a Artificial intelligence-enhanced software and systems engineering ; $v v. 6. $3 1481371
856 4 0 $u https://doi.org/10.1007/978-3-031-76572-8
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)