Machine learning for weekly work plan generation and enhanced constraint predication in last planner system (Softcopy is also available) (Record no. 72549)

MARC details
000 -LEADER
fixed length control field 02550nam a2200181Ia 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240906s9999 xx 000 0 und d
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number CEM TH-0457
Item number GAN
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Gandhi, Jaivik (PCM22145)
245 #0 - TITLE STATEMENT
Title Machine learning for weekly work plan generation and enhanced constraint predication in last planner system (Softcopy is also available)
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Date of publication, distribution, etc 2024
300 ## - PHYSICAL DESCRIPTION
Extent xviii,98p.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Abstract I<br/>Undertaking Iii<br/>Certificate V<br/>Acknowledgements Vii<br/>Abbreviations Ix<br/>Table Of Contents Xi<br/>List Of Figures Xiii<br/>List Of Tables Xv<br/>List Of Appendix Xvii<br/>Chapter-1: Introduction 1<br/>1.1 Need For The Study 1<br/>Chapter-2: Literature Review 3<br/>2.1.1 Lean Construction 3<br/>2.1.2 Last Planner System 4<br/>2.1.3 Machine Learning And Lean Construction 5<br/>2.1.4 Application Of Ml In Construction Industry 6<br/>2.1.5 Analysis Of Algorithms In Machine Learning 8<br/>2.1.6 Synthetic Data 9<br/>2.2 Previous Study 11<br/>2.3 Aims And Objectives 11<br/>2.4 Research Methodology For Research 12<br/>Chapter-3: Research Methodology 15<br/>3.1 Analysis Of The Research Methodology 15<br/>3.1.1 Literature Review 16<br/>3.1.2 Current Practices In Lps, Machine Learning And Synthetic Data Generation 16<br/>3.1.3 Data Collection 17<br/>3.1.4 Feature Selection 17<br/>3.1.5 Label Encoding 17<br/>3.1.6 Model For Synthetic Data Generation 17<br/>3.1.7 Developing The Prediction Model 18<br/>Chapter-4: Data Collection 19<br/>4.1 Data Of Super-Speciality Healthcare Project 19<br/>4.2 Constraint Log 19<br/>4.3 Constraints Analysis 20<br/>4.4 Data Collection Summary 21<br/>Chapter-5: Data Analysis 23<br/>5.1 Synthetic Data Generation 23<br/>5.2 Methods Used To Generate The Data 23<br/>5.2.1 Gretel.Ai 23<br/>5.2.2 Mostly.Ai 25<br/>5.2.3 Github (Synthetic Data Vault) 26 <br/>5.3 Synthetic Data Generation For Single Activity 26<br/>5.3.1 Development Of The Code For One Activity 27<br/>5.3.2 Final Code For All Activities 30<br/>5.4 Ml Model Preparation For Prediction 33<br/>5.4.1 Importing Various Library 33<br/>5.4.2 Files In Google Drive 34<br/>5.4.3 Training The Model 35<br/>5.5 Ml Model 1(Sgd) 37<br/>5.5.1 Output Of The Model 38<br/>5.5.2 Hyperparameter Tuning 38<br/>5.6 Testing The Model 39<br/>5.6.1 Final Output 40<br/>5.7 Ml Model 2(Multiout Regressor) 45<br/>5.7.1 Output Of The Model 47<br/>Chapter-6: Conclusion 51<br/>6.1 Future Scope 53<br/>References 55<br/>Appendix 61<br/>
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Devkar, Ganesh (Guide)
890 ## - Country
Country India
891 ## - Topic
Topic 2022 Batch
891 ## - Topic
Topic Construction engineering and Management
891 ## - Topic
Topic FT-PG
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      Not For Loan Faculty of Technology   CEPT Library CEPT Library 06/09/2024 Faculty of Technology CEM TH-0457 GAN 026666 06/09/2024 06/09/2024 Thesis
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