Luận văn thạc sĩ Quản lý xây dựng: Tối ưu hóa ước tính mức tiêu thụ năng lượng trong các tòa nhà dựa trên các thuật toán trí tuệ nhân tạo

HiӋn nay, tiӃt kiӋPQăQJOѭӧng là mӝt trong nhӳng vүQÿӅ cҩp thiӃt không chӍ trong phҥm vi tӯng quӕF JLD Pj ÿm WUӣ thành vҩQ ÿӅ cӫa toàn thӃ giӟi.. ThiӃt kӃ cӫa các tòa nhà hiӋn nay không c

Trang 1

7Ӕ,Ѭ8+Ï$ѬӞ&7Ë1+0Ӭ&7,Ç87+Ө1Ă1*/ѬӦ1* 7521*&È&7Ñ$1+¬'Ӵ$75Ç1&È&7+8Ұ772È1

/8Ұ19Ă17+Ҥ&6Ƭ

73+Ӗ&+Ë0,1+THÁNG 12 1Ă09

TP HỒ CHÍ MINH, tháng 01 năm 2020

Trang 2

ĈҤ,+Ӑ&48Ӕ&*,$7+¬1+3+Ӕ+Ӗ&+Ë0,1+

&iQEӝ+ѭӟQJGүQNKRDKӑFTS 7UҫQĈӭF+ӑF

&iQEӝFKҩPSKҧQELӋQ3*676/ѭѫQJĈӭF/RQJ

&iQEӝFKҩPSKҧQELӋQ76ĈLQK&{QJ7ӏQK

Trang 3

1- 7Ç1Ĉӄ7¬,

7Ӕ,Ѭ8+Ï$ѬӞ&7Ë1+0Ӭ&7,Ç87+Ө1Ă1*/ѬӦ1*7521*&È& 7Ñ$1+¬'Ӵ$75Ç1&È&7+8Ұ772È175Ë78ӊ1+Æ17Ҥ2

2- 1+,ӊ09Ө/8Ұ19Ă1

- Xác ÿӏQKÿѭӧFQKӳQJQKkQWӕҧQKKѭӣQJÿӃQQKXFҫXWLrXWKөQăQJOѭӧQJFӫDFiFWzDQKjFKXQJFѭWҥL73+ӗ&Kt0LQK

- ĈiQKJLi[ӃSKҥQJFiFQKkQWӕWӯÿyÿѭDUDÿѭӧFQKӳQJQKkQWӕҧQKKѭӣQJQKҩWÿӃQQKXFҫXWLrXWKөQăQJOѭӧQJFӫDFiFWzDQKjFKXQJFѭ

- Xâ\GӵQJP{KuQKѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJFӫDFiFWzDQKjFKXQJFѭEҵQJFiFWKXұWWRiQWUtWXӋQKkQWҥR

- ĈӅ[XҩWP{KuQKQKҵPWӕLѭXKyDѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJFӫDFiFWzDQKjFKXQJFѭEҵQJFiFKNӃWKӧSFiFP{KuQKWUtWXӋQKkQWҥR

75ѬӢNG KHOA KӺ THUҰT XÂY DӴNG

PGS.TS Lê Anh Tuҩn

Trang 4

/ӡL ÿҫX WLrQ W{L [LQ FKkQ WKjQK FҧP ѫQ VkX VҳF ÿӃQ ÿӃQ 76 7UҫQ ĈӭF +ӑF, 7Kҫ\ÿmWұQWuQKKѭӟQJGүQYjÿyQJJySQKLӅXêNLӃQTXêEiXWURQJVXӕWTXiWUuQKW{LWKӵF KLӋQOXұQYăQ 1KӳQJêNLӃQJySêKѭӟQJGүQ FӫD 7Kҫ\OjUҩWTXDQ WUӑQJFKRthàQKF{QJFӫDOXұQYăQQj\

;LQFKkQWKjQKFҧPѫQTXê7Kҫ\&{.KRD.ӻ7KXұW;k\'ӵQJ± EӝP{Q7KL

&{QJYj4XҧQOê;k\GӵQJÿmWUX\ӅQÿҥWQKӳQJNLӃQWKӭFEәtFKWURQJVXӕWWKӡLJLan W{LKӑFFKѭѫQJWUuQKFDRKӑF

;LQFҧPѫQFiFDQKFKӏEҥQEqFQJOӟS7 YjQKӳQJQJѭӡLEҥQDQKFKӏHPÿӗQJQJKLӋSÿmFKLDVҿNLQKQJKLӋPYjGjQKWKӡLJLDQKӛWUӧW{LWKӵFKLӋQWӕWJLDLÿRҥQNKҧR ViW Gӳ OLӋX WUѭӟF NKL WLӃQ KjQK QJKLrQ FӭX &iF FKLD Vҿ YӅ NLӃQ WKӭF Yj NLQKQJKLӋPFӫDFiFDQKFKӏFiFEҥQÿmÿѭӧFJKLQKұQYjRWKjQKTXҧFӫDOXұQYăQ

9jFXӕLFQJW{L[LQÿһFELӋWFҧPѫQÿӃQQKӳQJQJѭӡLWKkQWURQJgia ÿuQKÿmOX{QÿӗQJKjQKÿӝQJYLrQKӛWUӧYӅPӑLPһWÿӇW{L\rQWkPKRjQWKjQKWӕWOXұQYăQ

Trang 5

HiӋn nay, tiӃt kiӋPQăQJOѭӧng là mӝt trong nhӳng vүQÿӅ cҩp thiӃt không chӍ trong phҥm vi tӯng quӕF JLD Pj ÿm WUӣ thành vҩQ ÿӅ cӫa toàn thӃ giӟi 7KD\ ÿәi khí hұX Yj WăQJ JLi FiF ORҥL QăQJ Oѭӧng cùng vӟi chҩW Oѭӧng cuӝc sӕQJ FRQ QJѭӡi ngày càng cao nên càng phө thuӝc nhiӅu vào các nguӗQ QăQJ Oѭӧng ThiӃt kӃ cӫa các tòa nhà hiӋn nay không chӍ phҧi tҥo sӵ tiӋn nghi, thoҧLPiLFKRQJѭӡi sӱ dөng mà còn tӕi ѭXKyDVӱ dөQJQăQJOѭӧng và giҧm thiӇu tӕLÿDWiFÿӝng xҩXÿӕi vӟLP{LWUѭӡng.

/XұQYăQ WUuQKEj\NӃWTXҧFXӝFNKҧRViWQKӳQJQKkQWӕҧQKKѭӣQJÿӃQQKXFҫXWLrXWKөQăQJOѭӧQJFӫD WzDQKj FKXQJFѭ &XӝFNKҧR ViWÿѭӧFWKӵF KLӋQWK{QJTXDEҧQJFkXKӓLNKҧRViWYjSKkQWtFKVӕOLӋXWKӕQJNr.ӃWTXҧNKҧRViWÿm[ӃSKҥQJÿѭӧFcác tiêu chí ҧQKKѭӣQJÿӃQQKXFҫXWLrX WKө QăQJOѭӧQJFӫD WzDQKjFKXQJFѭ /XұQYăQÿmFKӍUDQKkQWӕҧQKKѭӣQJQKҩWÿӃQQKXFҫXWLrXWKөQăQJOѭӧQJFӫDWzDQKjFKXQJFѭ

7LӃSWKHROXұQYăQÿm[k\GӵQJP{KuQK P{KuQKGӵÿRiQPӭFWLrXWKөQăQJOѭӧQJFӫDWzDQKjFKXQJFѭ EҵQJWKXұWWRiQYӅWUtWXӋQKkQWҥR6ӱGөQJNLӇPFKӭQJchéo 10-IROGÿӇJLҧPWKLӇXVDLVӕOLrQTXDQÿӃQOҩ\PүXQJүXQKLrQWURQJTXiWUuQKÿjRWҥRĈiQKJLiFiFP{KuQKÿѫQWK{QJTXDFiFFKӍVӕWәQJKӧS6,7ӯÿyNӃWKӧSFiFP{KuQKFyKLӋXVXҩWWӕWQKҩWOҥLÿӇWӕLѭXKyDP{KuQKGӵÿRiQPӭFWLrXWKөQăQJOѭӧQJFӫDWzDQKjFKXQJFѭ

Trang 6

county but also of the world Because climete change and incresing prices of energy, along with improvement of the quality of life, so more and more depend on energy The design of current buildings not only creates comfort and convenience for people but also optimizes energy and minimizes negative impacts on the environment

This thesis show the results of the survey on factors affecting the energy consumption needs of apartment buildings The survey was conducted through survey questionnaires and statistical analysis The survey results have ranked the criteria affecting the energy consumption needs of the apartment building The thesis has showed 12 factors that most affect the energy consumption needs of apartment buildings

Then, this thesis has built models to predict energy consumption of apartment buildings by 6 algorithms on artificial intelligence Use 10-fold cross-validation to minimize errors related to random sampling during training Evaluate the single models by Synthesis index From there, combine the best performing models to optimize the predictive model of apartment building's energy consumption

Trang 7

7{L[LQFDPÿRDQOXұQYăQQj\GRFKtQKW{LWKӵFKLӋQGѭӟLVӵKѭӟQJGүQFӫD767UҫQĈӭF+ӑF&iFVӕOLӋXVӱGөQJSKkQWtFKWURQJOXұQYăQFyQJXӗQJӕFU}UjQJÿѭӧFWKXWKұSWӯTXiWUuQKNKҧRViWWKӵFWӃ YjÿѭӧFF{QJEӕWKHRÿ~QJTX\ÿӏQK

Tp.HCM, ngày tháng QăP

/r7ҩQ7jL

Trang 8

+97+/r7ҩQ7jL 1

MӨC LӨC

&+ѬѪ1*ĈҺ79Ҩ1Ĉӄ1*+,Ç1&Ӭ8 8

*,Ӟ,7+,ӊ8&+81* 8

ĈҺ79Ҩ1 Ĉӄ1*+,Ç1&Ӭ8 8

0Ө&7,Ç81*+,Ç1&Ӭ8 9

3+Ҥ09,1*+,Ç1&Ӭ8 9

ĈÏ1**Ï3'Ӵ.,ӂ1&Ӫ$1*+,Ç1&Ӭ8 9

9ӅPһWKӑFWKXұW 9

9ӅPһWWKӵFWLӉQ 10

&+ѬѪ1*7Ә1*48$1 11

7Ә1*48$19ӄ+ӊ7+Ӕ1*1Ă1*/ѬӦ1*9,ӊ71$0 11

7Ә1*48$19ӄ.+$,3+È'Ӳ/,ӊ8'$7$0,1,1* .12

ĈӏQKQJKƭD 12

&iFSKѭѫQJSKiSNKDLSKiGӳOLӋX 12

0Ҥ1*7+Ҫ1.,1+1+Æ17Ҥ2$11V .13

*LӟLWKLӋX 13

7KXұWWRiQP{KuQKPҥQJWKҫQNLQKQKkQWҥR 14

&Æ<3+Æ1/2Ҥ,+Ӗ,48<&$57 .15

*LӟL WKLӋX 15

7KXұWWRiQP{KuQKFk\SKkQORҥLKӗLTX\ 15

7ӴĈӜ1*3+È7+,ӊ17ѬѪ1*7È&&+,-SQUARED (CHAID) 16

*LӟLWKLӋX : 16

7KXұWWRiQP{KuQKWӵÿӝQJSKiWKLӋQWѭѫQJWiFFKL-squared 16

+Ӗ,48<78<ӂ17Ë1+/5 .17

2.6.*LӟLWKLӋX 17

Trang 9

+97+/r7ҩQ7jL 2

7KXұWWRiQP{KuQKKӗLTX\WX\ӃQWtQK 17

+Ӗ,48<78<ӂ17Ë1+7Ә1*48È7*(1/,1 .18

*LӟLWKLӋX 18

7KXұWWRiQP{KuQKKӗLTX\WX\ӃQWtQKWәQJTXiW 18

0È<+Ӛ75Ӧ9(&7Ѫ690 18

*LӟLWKLӋX 18

7KXұWWRiQP{KuQKPm\KӛWUӧYHFWѫ 19

0Ð+Î1+.ӂ7+Ӧ3(16(0%/(02'(/ .20

*LӟLWKLӋX : 20

7KXұWWRiQP{KuQKNӃWKӧS : 20

3+ѬѪ1*3+È3&52669$/,'$7,21 ,ӆ0&+Ӭ1*&+e2 21

2.10.1 *LӟLWKLӋX 21

2.10.2 ÈSGөQJSKѭѫQJSKiSNLӇPFKӭQJFKpR 21

&+ѬѪ1*3+ѬѪ1*3+È31*+,Ç1&Ӭ8 23

48<75Î1+1*+,Ç1&Ӭ8 23

3.1.1 *LDLÿRҥQ 23

3.1.2 *LDLÿRҥQ 24

3+ѬѪ1*3+È37+87+Ұ3'Ӳ/,ӊ8 24

3.2.1 ;iFÿӏQKQKӳQJQKkQWӕҧQKKѭӣQJÿӃQQKXFҫXWLrXWKөQăQJOѭӧQJ FӫDFăQKӝFKXQJFѭ 24

3.2.2 7KLӃWNӃEҧQJFkXKӓL 26

/é7+8<ӂ7.,ӆ0Ĉӎ1+7+$1*Ĉ2 28

&Ð1*&Ө1*+,Ç1&Ӭ8 30

3.4.1 3KҫQPӅPWKӕQJNr6366 30

3.4.2 3KҫQPӅP6366PRGHOHU&OHPHQWLQH 30

Trang 10

+97+/r7ҩQ7jL 3

&+ѬѪ1*7+87+Ұ39¬3+Æ17Ë&+'Ӳ/,ӊ8*,$,Ĉ2Ҥ1 31

7+87+Ұ3'Ӳ/,ӊ8 31

ĈҺ&Ĉ,ӆ0&Ӫ$0Ү81*+,Ç1&Ӭ8 31

6ӕQăPNLQKQJKLӋP 31

&KX\rQQJjQKYjOƭQKYӵFOjPYLӋF 32

.,ӆ0Ĉӎ1+&520%$&+¶6$/3+$ 33

4.1KyPQKkQWӕOLrQTXDQÿӃQNKtKұX 33

1KyPQKkQWӕOLrQTXDQÿӃQWKLӃWEӏVӱGөQJÿLӋQ 34

1KyPQKkQWӕOLrQTXDQÿӃQÿһFÿLӇPWzDQKj 34

1KyPQKkQWӕOLrQTXDQÿӃQÿһFÿLӇPFăQKӝ 35

1KyPQKkQWӕNKiF 36

;ӂ3+Ҥ1*0Ӭ&ĈӜҦ1++ѬӢ1*&È&1+Æ17Ӕ 37

&+ѬѪ1*7+87+Ұ3'Ӳ/,ӊ89¬;Æ<'Ӵ1*0Ð+Î1+'Ӵ%È2*,$, Ĉ2Ҥ1 39

7+87+Ұ3'Ӳ/,ӊ8 39

&Ҩ875Ò&;Æ<'Ӵ1*0Ð+Î1+ 41

6ѫÿӗTX\WUuQKWKӵFKLӋQ : 41

3KѭѫQJSKiSÿiQKJLiKLӋXVXҩWP{KuQK : 42

7+Ӵ&+,ӊ10Ð+Î1+ 43

3KkQFKLDYjQKұSGӳOLӋX 43

7K{QJVӕP{KuQK : 45

;k\GӵQJP{KuQKEҵQJ63660RGHOHU 46

.ӂ748Ҧ0Ð+Î1+ĈѪ1 47

7ұS'DWD6HW 47

Trang 11

+97+/r7ҩQ7jL 4

7ұS'ataSet 3: 48

7ұS'DWD6HW 48

7ұS'DWD6HW 49

7ұS'DWD6HW 50

7әQJKӧSNӃWTXҧFKӍVӕÿiQKJLi 50

7әQJKӧSNӃWTXҧKӋVӕGӵEiRWҫPTXDQWUӑQJ 51

.ӂ748Ҧ0Ð+Î1+7Ә1*+Ӧ3 54

3KѭѫQJSKiS : 54

.ӃWTXҧ 56

7әQJKӧS 58

6RViQKJLӳDFiFP{KuQKÿѫQYjP{KuQKNӃWKӧS 59

&+ѬѪ1*.ӂ7/8Ұ19¬.,ӂ11*+ӎ 62

.ӂ7/8Ұ1 62

.,ӂ11*+ӎ 63

Trang 12

+97+/r7ҩQ7jL 5

'$1+0Ө&%Ҧ1*%,ӆ8

%ҧQJ&iFQKkQWӕҧQKKѭӣQJÿӃQQKXFҩXWLrXWKөQăQJOѭӧQJFӫDFăQKӝ

FKXQJFѭ 25

%ҧQJ3KkQQKyPFiFQKkQWӕҧQKKѭӣQJÿӃQQKXFҩXWLrXWKөQăQJOѭӧQJFӫD FăQKӝFKXQJFѭ 27

%ҧQJ7KӕQJNrVӕQăPNLQKQJKLӋPFӫDQJѭӡLWKDP JLDNKҧRViW 31

%ҧQJ7KӕQJNrFKX\rQQJjQKYjOƭQKYӵFOjPYLӋFFӫDQJѭӡLWKDPJLDNKҧR sát 32

%ҧQJ+ӋVӕ&URPEDFK¶VDOSKDFKRWѭӡQJQKyPQKkQWӕ 33

%ҧQJ+ӋVӕ&URPEDFK¶VDOSKDQKyPQKkQWӕOLrQTXDQÿӃQNKtKұX 33

%ҧQJ+ӋVӕ&URPEDFK¶VDOSKDQKyPQKkQWӕOLrQTXDQÿӃQWKLӃWEӏVӱGөQJ ÿLӋQ 34

%ҧQJ+ӋVӕ&URPEDFK¶VDOSKDQKyPQKkQWӕOLrQTXDQÿӃQÿһFÿLӇPWzDQKj .35

%ҧQJ+ӋVӕ&URPEDFK¶VDOSKDQKyPQKkQWӕOLrQTXDQÿӃQÿһFÿLӇPFăQKӝ .36

%ҧQJ+ӋVӕ&URPEDFK¶VDOSKDQKyPQKkQWӕNKiF 36

%ҧQJ.ӃWTXҧ[ӃSKҥQJPӭFÿӝҧQKKѭӣQJFӫDFiFQKkQWӕ 37

%ҧQJ1KӳQJQKkQWӕҧQKKѭӣQJQKҩWÿӃQQKXFҫXWLrXWKөQăQJOѭӧQJWURQJ FăQKӝFKXQJFѭ 39

%ҧQJ0{WҧGӳOLӋX 40

%ҧQJ7KLӃWOұSWK{QJVӕPһFÿӏQKWURQJ&OHPHQWLQH 45

%ҧQJ.ӃWTXҧFKӍVӕÿiQKJLiP{KuQKYӟLWұS7HVWLQJ 47

%ҧQJ.ӃWTXҧFKӍVӕÿiQKJLiP{KuQKYӟLWұp Testing 2 47

Trang 13

+97+/r7ҩQ7jL 6

%ҧQJ.ӃWTXҧFKӍVӕÿiQKJLiP{KuQKÿѫQ 50

%ҧQJ.ӃWTXҧFKӍVӕÿiQKJLiP{KuQKWәQJKӧSYӟLWұS7HVWLQJ 56

%ҧQJ.ӃWTXҧWәQJKӧSFKӍVӕÿiQKJLiP{KuQKWәQJKӧS 58

%ҧQJ6RViQKFKӍVӕJLӳDFiFP{KuQKÿѫQYjP{KuQKNӃWKӧS 59

Trang 14

+97+/r7ҩQ7jL 7

'$1+0Ө& HÌNH 9Ӏ

+uQK7ӍWUӑQJWLrXWKөQăQJOѭӧQJFӫD9LӋW1DP 8

+uQK7ӕFÿӝWăQJWUѭӣQJÿLӋQWKѭѫQJSKҭm và GDP (%) 11

+uQK7әQJTXDQYӅFiFEѭӟFWURQJTXiWUuQK.'' 12

Hình 2.3 Mô hình ANN 14

+uQK9tGөFk\TX\ӃWÿӏQK 15

+uQK0{KuQKKӗLTX\ÿѫQ 17

+uQK0i\KӛWUӧYHFWѫKӗLquy 19

+uQK3KѭѫQJSKiS[iFWKӵFFKpROҫQ 22

+uQK4X\WUuQKQJKLrQFӭXJLDLÿRҥQ 23

+uQK6ѫÿӗNKӕLP{KuQKӭFWtQKPӭFWLrXWKөQăQJOѭӧQJ 24

+uQK%LӇXÿӗFѫFҩXVӕQăPNLQKQJKLӋPFӫDQJѭӡLWKDPJLDNKҧRViW 31

+uQK%LӇXÿӗFѫFҩXFKX\rQQJjQKYjOƭQKYӵOjPYLӋFFӫDQJѭӡLWKDPJLD NKҧRViW 32

+uQK6ѫÿӗFiFEѭӟF[k\GӵQJP{KuQKGӵEiREҵQJ63660RGHOHU 41

Hình 5.2 3KkQFKLDWұSGӳOLӋXYӟL- fold 43

+uQK*iQWұS7UDQLQJ'DWD6HWYjR&OHPHQWLQH 44

+uQK;k\GӵQJP{KuQKÿѫQ 46

+uQK7әQJKӧSKӋVӕGӵEiRWҫPTXDQWUӑQJP{KuQK$11V 51

+uQK7әQJKӧSKӋVӕGӵEiRWҫPTXDQWUӑQJP{KuQK&$57 52

+uQK7әQJKӧSKӋVӕGӵEiRWҫPTXDQ WUӑQJP{KuQK&+$,' 52

+uQK7әQJKӧSKӋVӕGӵEiRWҫPTXDQWUӑQJP{KuQK/5 53

+uQK7әQJKӧSKӋVӕGӵEiRWҫPTXDQWUӑQJP{KuQK*(1/,1 53

+uQK7әQJKӧSKӋVӕGӵEiRWҫPTXDQWUӑQJP{KuQK690 54

+uQK;k\GӵQJP{KuQKNӃWKӧS 55

+uQK%LӇXÿӗKӋVӕWѭѫQJTXDWX\ӃQWtQK5JLӳDFiFP{KuQK 59

+uQK%LӇXÿӗSKҫQWUăPVDLVӕWUXQJEuQK0$3(JLӳDFiFP{KuQK 60

+uQK%LӇXÿӗVDLVӕWUXQJEuQKWX\ӋWÿӕL0$(JLӳDFiFP{KuQK 60

+uQK%LӇXÿӗVDLVӕWRjQSKѭѫQJWUXQJEuQK506(JLӳDFiFP{KuQK 61

Trang 15

+97+/r7ҩQ7jL 8

&+ѬѪ1* ĈҺ79Ҩ1Ĉӄ1*+,Ç1&Ӭ8 1.1 GIӞ, THIÊ ҕ U CHUNG

HiӋn nay, tiӃt kiӋP QăQJ Oѭӧng là mӝt trong nhӳng vүQ ÿӅ cҩp thiӃt không chӍ trong phҥm vi tӯng quӕFJLDPjÿmWUӣ thành vҩQÿӅ cӫa toàn thӃ giӟi [1]7KD\ÿәi khí hұXYjWăQJJLiFiFORҥLQăQJOѭӧng cùng vӟi chҩWOѭӧng cuӝc sӕQJFRQQJѭӡi ngày càng cao nên càng phө thuӝc nhiӅu vào các nguӗQQăQJOѭӧQJÿmWҥo ra nhӳng thách thӭc cho ÿӝLQJǊNLӃQWU~FVѭNӻ VѭSKҧi không ngӯng sáng tҥo và cҧi tiӃn các thiӃt kӃ trong ngành xây dӵng ThiӃt kӃ cӫa các tòa nhà hiӋn nay không chӍ phҧi tҥo sӵ tiӋn nghi, thoҧi PiLFKRQJѭӡi sӱ dөng mà còn tӕLѭXKyDVӱ dөQJQăQJOѭӧng và giҧm thiӇu tӕLÿDWiFÿӝng xҩXÿӕi vӟLP{LWUѭӡng

7UrQWKӃJLӟLQăQJOѭӧQJVӱGөQJWURQJFiFWzDQKjFKLӃPÿӃQFӫDWәQJQăQJOѭӧQJ[2]Ӣ9LӋW1DPWӹOӋQj\Oj[3]5LrQJÿӕLYӟL0ӻYjFiFQѭӟF&KkXÆXWӹOӋQj\FKLӃPÿӃQ[4]'RÿyYLӋFѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJWURQJFic tòa QKjFyêQJKƭDUҩWTXDQWUӑQJWURQJYLӋFWӕLѭXKyDKLӋXVXҩWVӱGөQJQăQJOѭӧQJQKҵPPөFÿtFKWLӃWNLӋPQăQJOѭӧQJYjJLҧPWKLӇXWiFÿӝQJÿӕLYӟLP{LWUѭӡQJ

Hình 1.17ӍWUӑQJWLrXWKөQăQJOѭӧQJFӫD9LӋW1DP

1.2 ĈҺ7 9Ҩ1 Ĉӄ NGHIÊN &Ӭ8

+ӋWKӕQJQăQJOѭӧQJWURQJWzDQKjWѭѫQJÿӕLSKӭFWҥSÿӕLYӟLWӯQJF{QJWUuQKQKҩWÿӏQK[5]&iFWKLӃWEӏWLrXWKөQăQJOѭӧQJFKӫ\ӃXWURQJWzDQKjQKѭKӋWKӕQJWKLӃWEӏÿLӅXKzDNK{QJNKtWӫOҥQKEӃSÿLӋQ[6].tFKWKѭӟFSKzQJYjÿһFÿLӇPFӱDVәFǊQJ

ƀŶŐŶŐŚŝҵƉ 42%

EŚăӂ 27%

7KѭѫQJPҥLYjGӏFK

YөF{QJFӝQJ

22%

sҨŶĐŚƵǇҳŶ 2%

Khác 7%

2018

Trang 16

+97+/r7ҩQ7jL 9

ÿѭӧFWKD\ÿәLWKHRWӯQJORҥLF{QJWUuQK[5]1JRjLUDFiF\ӃXWӕYӅÿLӅXNLӋQWKӡLWLӃWFǊQJJk\ҧQKKѭӣQJNK{QJQKӓÿӕLYӟLQKXFҫXVӱGөQJQăQJOѭӧQJFӫDWzDQKj[1] 'RVӵSKӭFWҥSҩ\QrQYLӋFѭӟFWtQKFKtQK[iFPӭFWLrXWKөQăQJOѭӧQJWURQJWzDQKj JһS QKLӅX NKy NKăQ 7URQJ QKӳQJ QăP JҫQ ÿk\ ÿm Fy UҩW QKLӅX QJKLrQ FӭX YӅSKѭѫQJSKiSGӵÿRiQÿmÿѭӧFÿӅ[XҩWYjiSGөQJUӝQJUmLFKRUҩWQKLӅXQJjQKQJKӅ1KӳQJSKѭѫQJSKiSQj\EDRJӗPFiFSKѭѫQJSKiSNӻWKXұWWKӕQJNrYjWUtWXӋQKkQWҥR

0өFWLrXWәQJTXiWFӫDÿӅWjLWӕLѭXKyDѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJWURQJFiFWzDQKjGӵDWUrQFiFWKXұWWRiQWUtWXӋQKkQWҥR

Trang 17

+97+/r7ҩQ7jL 10

ĈѭDUDFiFP{KuQKѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJFӫDFiFWzDQKjFKXQJFѭEҵQJFiFWKXұWWRiQWUtWXӋQKkQWҥR

ĈӅ[XҩWP{KuQKQKҵPWӕLѭXKyDѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJFӫDFiFWzDQKjFKXQJFѭEҵQJFiFKNӃWKӧSFiFWKXұWWRiQWUtWXӋQKkQWҥR

1.5.2 9ӅPһWWKӵFWLӉQ

ĈӅWjLJL~SJLҧLTX\ӃWÿѭӧFEjLWRiQTXҧQOêYjWLӃWNLӋPQăQJOѭӧQJWURQJFiFWzDQKjFKXQJFѭĈѭDUDP{KuQKWӕLѭXKyDѭӟFWtQKPӭFWLrXWKөQăQJOѭӧQJÿLӋQWURQJFiFFăQJKӝFKXQJFѭWK{QJTXDFiFQKkQWӕFKtQKҧQKKѭӣQJWӟLQy

*ySSKҫQQkQJFDRKLӋXTXҧYӅTXҧQOêWKLӃWNӃWKLF{QJQKҵPWLӃWNLӋPQăQJOѭӧQJFKXQJ WD\EҧRYӋP{LWUѭӡQJYuVӵSKiWWULӇQEӅQYӳQJFӫDWKӃJLӟLQyLFKXQJYj9LӋW1DPQyLULrQJ

ĈӅ[XҩWQKӳQJJLҧLSKiSYӅNLӃQWU~F[k\GӵQJQKҵPWLӃWNLӋPQăQJOѭӧQJWURQJTXiWUuQKYұQKjQKWzDQKj

;k\GӵQJP{KuQKQKҵPTXҧQOêQăQJOѭӧQJFKRFiFWzDQKjFKXQJFѭ

Trang 18

+97+/r7ҩQ7jL 11

&+ѬѪ1* 7Ә1*48$1

7URQJKѫQKDLWKұp kӹ vӯa qua, ViӋt Nam là mӝt trong nhӳQJQѭӟc có tӕFÿӝ WăQJWUѭӣng kinh tӃ FDRKjQJÿҫu thӃ giӟi, tәng sҧn phҭm quӕc nӝL*'3