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Vietnam is a country that is assessed to have a lot of potential in creating solar energy
sources, the number of solar power projects is increasingly spreading across the country.
However, making investment decisions based on project efficiency as well as construction
management of solar energy projects and project infrastructure is still new. In the context
of this development, students have conducted surveys and researched the factors affecting
the efficiency or productivity of a solar power project.
By studying previous studies, papers and surveying the experts, the study identified
16 factors that directly affect the productivity of a solar power plant construction project in
Vietnam, such as: The responsiveness of the local power grid, the intensity of light and the
intensity of solar radiation emitted, the elevation of the construction terrain,« etc. These
factors will be an important reference base for Investors evaluate the initial potential when
intending to invest in a solar power project.
Beside of finding out 16 factors affecting the productivity of solar power systems,
the study also optimizes the predictive performance of solar power systems by using
Clementine software (or also known as IBM SPSS Modeler) applies six single artificial
intelligence models including: linear regression (LR), generalized linear regression
(GENLIN), artificial neural network (ANN), support vector machine (SVM), Classification
and regression trees (CART) and Chi ± Squared automatic interaction detection (CHAID)
to conduct the analysis to exploit the data collected from the Global Solar Atlas website .
Six models were used independently to mine the collected data, by performing crossvalidation using the k-fold model. Six single models with 10 data files are evaluated through
the SI performance factor from which students continue to create four combinated models
that combine the best performing single models to optimize results predicting the yield of a
solar power construction project.
The results show that for the single model group, the two models with the best predictive
results are SVM and ANN, and the two models with the worst results are GENLIN and
CHAID. The combined model MH2 is combined from the SVM and ANN models, giving
the optimal results that are superior to the previous single models.
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2.7.7. 0{KuQKKӗLTX\WX\ӃQWtQKWәQJTXiW *HQHUDO/LQHDU5HJUHVVLRQ- GenLin) .......... 22
2.7.8. 0{KuQKFk\SKkQORҥLYjKӗLTX\ &ODVVLILFDWLRQDQG5HJUHVVLRQ7UHH± CART) .... 23
2.7.9. 0{KuQKWӵÿӝQJSKiWKLӋQWѭѫQJWiF&KL± squared (CHAID) .................................. 25
2.7.10. Mô hình NӃWKӧS (QVHPEOHPRGHO ......................................................................... 25
3+ѬѪ1*3+È3.,ӆ0&+Ӭ1*&+e2 &52669$/,'$7,21 ...................26
2.8.1. *LӟLWKLӋXFKXQJYӅSKѭѫQJSKiSNLӇPFKӭQJFKpR ................................................. 26
2.8.2. ÈSGөQJNLӇPFKӭQJFKpR ......................................................................................... 27
3+ѬѪ1*3+È31*+,Ç1&Ӭ8 .............................................................. 28
48<75Î1+1*+,Ç1&Ӭ8.................................................................................28
7+87+Ұ3'Ӳ/,ӊ8 ............................................................................................31
3.2.1. 7KXWKұSFiFQKkQWӕҧQKKѭӣQJÿӃQQăQJVXҩWҧQKKѭӣQJÿӃQQăQJVXҩWKӋWKӕQJÿLӋQ
PһWWUӡL ................................................................................................................................ 31
3.2.2. 7KLӃWNӃEҧQJFkXKӓL ................................................................................................. 33
3.2.3. .KҧRViWYjWKXWKұSGӳOLӋX ...................................................................................... 36
7+$1*Ĉ29¬.,ӆ0Ĉӎ1+7+$1*Ĉ2 ........................................................37
3.3.1. 3KkQWtFKÿӝWLQFұ\&URQEDFK
V$OSKD ....................................................................... 37
3.3.2. 3KkQWtFKQKkQWӕNKiPSKi()$ ............................................................................... 38
*,Ӟ,7+,ӊ8&Ð1*&Ө1*+,Ç1&Ӭ8 ..............................................................40
3.4.1. 3KҫQPӅPSKkQ WtFKWKӕQJkê IBM SPSS .................................................................. 40
3.4.2. 3KҫQPӅP NKDLWKiFGӳOLӋX,%063660RGHOHU± Clementine. ............................... 40
3+Æ17Ë&+'Ӳ/,ӊ8 ............................................................................. 42
3+Æ17Ë&+ĈҺ&Ĉ,ӆ0'Ӳ/,ӊ81*+,Ç1&Ӭ8 ..........................................42
ĈҺ&Ĉ,ӆ00Ү81*+,Ç1&Ӭ8 ........................................................................42
4.2.1. &KX\rQQJjQKOjPYLӋFFӫDÿӕLWѭӧQJWKDPJLDNKҧRViW ......................................... 42
4.2.2. 6ӕQăPNLQKQJKLӋPWURQJOƭQKYӵFOjPYLӋF ............................................................. 43
4.2.3. 9ӏWUtOjPYLӋFFӫDÿӕLWѭӧQJWKDPJLDNKҧRViW ........................................................ 44
4.2.4. 7KӡLJLDQOjPYLӋFWURQJOƭQKYӵFQăQJOѭӧQJWiLWҥR ................................................ 45
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.,ӆ0Ĉӎ1+&521%$&+¶6$/3+$ ..................................................................46
4.3.1. Nhóm I - Các QKkQWӕOLrQTXDQÿӃQTX\KRҥFKYj[k\GӵQJ..................................... 47
4.3.2. Nhóm II ± Các QKkQWӕOLrQTXDQÿӃQWKӡLWLӃWYjYӏWUtÿӏDOê .................................... 48
4.3.3. Nhóm III ± Các QKkQWӕOLrQTXDQÿӃQNӻWKXұWFӫDKӋWKӕQJÿLӋQPһWWUӡL .............. 49
4.3.4. Nhóm IV - CiFQKkQWӕOLrQTXDQÿӃQFKҩWOѭӧQJFӫDKӋWKӕQJÿLӋQPһWWUӡL ........... 49
4.3.5. Nhóm V - CiFQKkQWӕOLrQTXDQÿӃQYұQKjQKKӋWKӕQJÿLӋQPһWWUӡL ..................... 50
3+Æ17Ë&+1+Æ17Ӕ.+È03+È()$ .........................................................51
;ӂ3+Ҥ1*0Ӭ&ĈӜҦ1++ѬӢ1*&È&1+Æ17Ӕ ......................................55
0Ð+Î1+1*+,Ç1&Ӭ89¬.ӂ748Ҧ7Ӕ,Ѭ8 ............................... 58
;Æ<'Ӵ1*0Ð+Î1+1*+,Ç1&Ӭ8 ..............................................................58
5.1.1. ;k\GӵQJP{KuQKQJKLrQFӭX ................................................................................... 58
5.1.2. 'ӳOLӋXQJKLrQFӭu ..................................................................................................... 59
5.1.3. 3KѭѫQJSKiSÿiQKJLiKLӋXVXҩWP{KuQK KXҩQOX\ӋQ ................................................ 61
7+Ӵ&+,ӊ10Ð+Î1+ ........................................................................................62
5.2.1. PhâQFKLDFKLDGӳOLӋXWKjQK± fold ....................................................................... 62
5.2.2. .KDLEiRFiFWK{QJVӕFKRFiFmô hình. .................................................................... 64
5.2.3. ;k\GӵQJP{KuQKWURQJ&OHPHQWLQH ......................................................................... 67
.ӂ748Ҧ7Ӕ,Ѭ80Ð+Î1+ĈѪ1 ...................................................................68
5.3.1. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 68
5.3.2. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 68
5.3.3. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 68
5.3.4. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 69
5.3.5. .ӃWXҧÿiQKJLiIROG................................................................................................. 69
5.3.6. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 70
5.3.7. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 70
5.3.8. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 70
5.3.9. .ӃWTXҧÿiQKJLiIROG .............................................................................................. 71
5.3.10. .ӃWTXҧÿiQKJLiIROG........................................................................................... 71
5.3.11. .ӃWTXҧÿiQKJLiWәQJKӧS ....................................................................................... 71
5.3.12. .ӃWTXҧWәQJKӧSKӋVӕÿiQKJLiPӭFÿӝTXDQWUӑQJFӫDELӃQ 9DULDEOH,PSRUWDQFH
.............................................................................................................................................. 72
.ӂ748ҦĈÈ1+*,È0Ð+Î1+.ӂ7+Ӧ3 ......................................................75
5.4.1. ;k\GӵQJP{KuQKNӃWKӧS ........................................................................................ 75
5.4.2. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ ............................................. 76
HVTH:rLêr+ҧLrĈăQJ
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5.4.3. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ2 ............................................. 77
5.4.4. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ3 ............................................. 77
5.4.5. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ4 ............................................. 77
5.4.6. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ5 ............................................. 78
5.4.7. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧS WұSKXҩQOX\ӋQVӕ6 ............................................. 78
5.4.8. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ7 ............................................. 78
5.4.9. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ8 ............................................. 78
5.4.10. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ9 ........................................... 79
5.4.11. .ӃWTXҧÿiQKJLiP{KuQKNӃWKӧSWұSKXҩQOX\ӋQVӕ0 ......................................... 79
5.4.12. .ӃWTXҧÿiQKJLiWәQJKӧSFiFFKӍVӕFӫDP{KuQKNӃWKӧS. .................................... 79
626È1+.ӂ748Ҧ*,Ӳ$0Ð+Î1+ĈѪ19¬0Ð+Î1+.ӂ7+Ӧ3 .........80
.ӂ7/8Ұ1 ................................................................................................ 84
.ӂ7/8Ұ1 .............................................................................................................84
.,ӂ11*+ӎ+ѬӞ1*1*+,Ç1&Ӭ87ѬѪ1*/$, ...........................................85
'$1+0Ө&&Ð1*75Î1+Ĉ&Ð1*%Ӕ.................................................................. 86
7¬,/,ӊ87+$0.+Ҧ2 ................................................................................................. 87
3+Ө/Ө&........................................................................................................................... 91
3+Ө/Ө&- %Ҧ1*&Æ8+Ӓ,.+Ҧ26È7&È&1+Æ17ӔҦ1++ѬӢ1* ........91
3+Ө/Ө&± .ӂ748Ҧ.,ӆ0Ĉӎ1+&521%$&+¶6$/3+$ ..............................98
3+Ө/Ө&- .ӂ748Ҧ3+Æ17Ë&+()$ ..............................................................103
3+Ө/Ө&± %Ӝ'Ӳ/,ӊ86Ӱ'Ө1*&+21*+,Ç1&Ӭ8*,$,Ĉ2Ҥ1 .......113
3+Ө/Ө&- .ӂ748Ҧ7Ӕ,Ѭ8'ӴĈ2È11Ă1*68Ҩ7+ӊ7+Ӕ1*Ĉ,ӊ11Ă1*
/ѬӦ1*0Һ775Ӡ,7Ӯ&È&0Ð+Î1+ .................................................................122
'$1+6È&+&È&&+8<Ç1*,$7+$0*,$.+Ҧ26È7 ..................................... 172
/é/ӎ&+75Ë&+1*$1* ............................................................................................. 173
HVTH:rLêr+ҧLrĈăQJ
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GVHD: TS. 1JX\ӉQĈăQJ7UuQK - 3*6767UҫQĈӭF+ӑF
'$1+0Ө&+Î1+Ҧ1+
Hunh 1.1. Công suҩt lҳSÿһWQăQJOѭӧng mһt trӡi khu vӵc ASEAN tӯ 2010 - 2019[2] .......2
Hunh 2.1. BiӇXÿӗ sӵ phát triӇQQăQJOѭӧng khu vӵF$6($1JLDLÿRҥn 2005 ± 2040[2] ...6
Hunh 2.2. BҧQJÿӗ công suҩWÿLӋn mһt trӡi tҥi mӝt sӕ tӍnh thành.[4]...................................7
Hunh 2.3. Ӭng dөng cӫD$,WURQJQăQJOѭӧng tái tҥo ........................................................10
Hunh 2.4. Mô hình hóa quy trình cӫa trí tuӋ nhân tҥo ........................................................15
Hunh 2.5. Mô hình phân loҥi các thuұt toán Machine learning..........................................17
Hunh 2.6. Mô hình thuұt toán ANN ...................................................................................19
Hunh 2.7. Mô hình thuұt toán SVM ...................................................................................21
HuQK0{KuQKSKѭѫQJSKiSNLӇm chӭng chéo ...........................................................27
Hunh 3.1. 6ѫÿӗ khӕi quy trình nghiên cӭXJLDLÿRҥn 1. ....................................................29
Hunh 3.2. 6ѫÿӗ khӕi quy trình nghiên cӭXJLDLÿRҥn 2. ....................................................30
Hunh 4.1. BiӇXÿӗ thӇ hiӋQFѫFҩu chuyên ngành cӫDÿӕLWѭӧng tham gia khҧo sát. ........43
Hunh 4.2. BiӇXÿӗ thӇ hiӋQFѫFҩu sӕ QăPÿӕLWѭӧng tham gia khҧo sát. ........................44
Hunh 4.3. BiӇXÿӗ thӇ hiӋQFѫFҩu vӏ trí làm viӋc cӫDÿӕLWѭӧng tham gia khҧo sát. .........45
Hunh 4.4.. BiӇXÿӗ thӇ hiӋQFѫFҩu thӡi gian làm viӋFWURQJOƭQKYӵFQăQJOѭӧng tái tҥo cӫa
ÿӕLWѭӧng tham gia khҧo sát. ..............................................................................................46
Hunh 5.1. /ѭXÿӗ mô hình nghiên cӭu. ..............................................................................58
Hunh 5.2. 6ѫÿӗ phân chia dӳ liӋu thành 10 ± fold ............................................................62
Hunh 5.3. Nhұp tұp dӳ liӋu sӕ 1 vào mô hình Clementine khai báo các thông sӕ ............63
Hunh 5.4. Gán dӳ liӋu huҩn luyӋn vào mô hình Clementine ............................................64
Hunh 5.5. Ví dө khai báo cho mô hình SVM ....................................................................67
Hunh 5.6. Mô hình huҩn luyӋQÿѫQWURQJ&OHPHQWLQH ......................................................67
Hunh 5.7. BiӇXÿӗ thӇ hiӋn chӍ sӕ ÿiQKJLiPӭFÿӝ quan trӑng cӫa biӃn mô hình SVM .72
Hunh 5.8. BiӇXÿӗ thӇ hiӋn chӍ sӕ ÿiQKJLiPӭFÿӝ quan trӑng cӫa biӃn mô hình ANN .73
Hunh 5.9. BiӇXÿӗ thӇ hiӋn chӍ sӕ ÿiQKJLiPӭFÿӝ quan trӑng cӫa biӃn mô hình GENLIN
............................................................................................................................................73
Hunh 5.10. BiӇu ÿӗ thӇ hiӋn chӍ sӕ ÿiQKJLiPӭFÿӝ quan trӑng cӫa biӃn mô hình LR ...74
Hunh 5.11. BiӇXÿӗ thӇ hiӋn chӍ sӕ ÿiQKJLiPӭFÿӝ quan trӑng cӫa biӃn mô hình CART
............................................................................................................................................75
Hunh 5.12. BiӇXÿӗ thӇ hiӋn chӍ sӕ ÿiQKJLiPӭFÿӝ quan trӑng cӫa biӃn mô hình CHAID
............................................................................................................................................75
HVTH:rLêr+ҧLrĈăQJ
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/XұQrYăQrWӕWrQJKLӋSrWKҥFVƭ
GVHD: TS. 1JX\ӉQĈăQJ7UuQK - 3*6767UҫQĈӭF+ӑF
Hunh 5.13. Mô hình huҩn luyӋn kӃt hӧp trong Clementine ...............................................76
Hunh 5.14. BiӇXÿӗ thӇ hiӋn hӋ sӕ hiӋu suҩt tәng hӧp SI cӫa các mô hình .......................81
Hunh 5.15. BiӇXÿӗ thӇ hiӋn hӋ sӕ TQTT R cӫa các mô hình ............................................82
Hunh 5.16. BiӇXÿӗ thӇ hiӋn MAPE cӫa các mô hình ........................................................82
Hunh 5.17. BiӇXÿӗ thӇ hiӋn MAE cӫa các mô hình ..........................................................83
Hunh 5.18. BiӇXÿӗ thӇ hiӋn RMSE cӫa các mô hình ........................................................83
HVTH:rLêr+ҧLrĈăQJ
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Bҧng 2.1. Thӕng kê sӕ giӡ nҳQJWURQJQăPWҥi mӝt sӕ vùng trên cҧ Qѭӟc. .........................5
Bҧng 2.2. MөFWLrXQăQJOѭӧng tái tҥo tҫm nhìn 2030 ........................................................8
Bҧng 2.3. Bҧng các nhân tӕ ÿӅ xuҩt ҧQKKѭӣQJÿӃQQăQJVXҩt hӋ thӕQJÿLӋQQăQJOѭӧng
mһt trӡi ...............................................................................................................................13
Bҧng 3.1. Bҧng các nhân tӕ ҧQKKѭӣQJÿӃQQăQJVXҩt hӋ thӕQJÿLӋQQăQJOѭӧng mһt trӡi
............................................................................................................................................31
Bҧng 3.2. MӭFÿӝ ҧQKKѭӣng cӫa các nhân tӕ ...................................................................33
Bҧng 3.3. MӭFÿӝ ҧQKKѭӣng cӫa các nhân tӕ ...................................................................34
Bҧng 3.4. Giá trӏ tiêu chuҭn cӫa hӋ sӕ tҧLWѭѫQJӭng vӟLNtFKWKѭӟc mүu ........................39
Bҧng 4.1. Thӕng kê chuyên ngành làm viӋc cӫDQJѭӡi tham gia khҧo sát........................42
Bҧng 4.2. Thӕng kê sӕ QăPNLQKQJKLӋm làm viӋc cӫDQJѭӡi tham gia khҧo sát .............43
Bҧng 4.3. Thӕng kê vӏ trí làm viӋc cӫDQJѭӡi tham gia khҧo sát ......................................44
Bҧng 4.4. Thӕng kê thӡi gian làm viӋc WURQJOƭQKYӵFQăQJOѭӧng tái tҥo cӫa cӫDQJѭӡi
tham gia khҧo sát ...............................................................................................................45
Bҧng 4.5. KӃt quҧ kiӇPÿӏQK&URQEDFK¶V$OSKDÿӕi vӟi tӯng nhóm nhân tӕ ...................46
Bҧng 4.6. HӋ sӕ &URQEDFK¶V$OSKDQKyPQKkQWӕ OLrQTXDQÿӃn quy hoҥch và xây dӵng47
Bҧng 4.7. HӋ sӕ &URQEDFK¶V$OSKDQKyPQKkQWӕ OLrQTXDQÿӃn thӡi tiӃt và vӏ WUtÿӏa lý .48
Bҧng 4.8. HӋ sӕ &URQEDFK¶V$OSKDQKyPQKkQWӕ OLrQTXDQÿӃn kӻ thuұt cӫa hӋ thӕQJÿLӋn
mһt trӡi ...............................................................................................................................49
Bҧng 4.9. HӋ sӕ &URQEDFK¶V$OSKDQKyPQKkQWӕ OLrQTXDQÿӃn chҩWOѭӧng cӫa hӋ thӕng
ÿLӋn mһt trӡi .......................................................................................................................50
Bҧng 4.10. HӋ sӕ &URQEDFK¶V$OSKDQKyPQKkQWӕ OLrQTXDQÿӃn vұn hành hӋ thӕQJÿLӋn
mһt trӡi ...............................................................................................................................51
Bҧng 4.11. KӃt quҧ kiӇPÿӏQK.02Yj%DUWOHWW¶V ............................................................52
Bҧng 4.12. KӃt quҧ phân tích nhân tӕ ...............................................................................52
Bҧng 4.13. Bҧng xӃp hҥng mӭFÿӝ ҧQKKѭӣng cӫa các nhân tӕ ÿӃQQăQJVXҩt cӫa hӋ thӕng
ÿLӋQQăQJOѭӧng mһt trӡi. ...................................................................................................55
Bҧng 5.1. Bҧng xӃp hҥng các nhân tӕ ҧQKKѭӣng nhiӅu nhҩWÿӃQQăQJVXҩt hӋ thӕQJÿLӋn
QăQJOѭӧng mһt trӡi ............................................................................................................59
Bҧng 5.2. Các nhân tӕ ÿѭӧc chӑn phөc vө thu thұp dӳ liӋXJLDLÿRҥn 2 ...........................60
Bҧng 5.3. Bҧng các thông sӕ khai báo mô hình .................................................................64
HVTH:rLêr+ҧLrĈăQJ
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/XұQrYăQrWӕWrQJKLӋSrWKҥFVƭ
GVHD: TS. 1JX\ӉQĈăQJ7UuQK - 3*6767UҫQĈӭF+ӑF
Bҧng 5.4. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ....................................68
Bҧng 5.5. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ....................................68
Bҧng 5.6. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ....................................68
Bҧng 5.7. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ....................................69
Bҧng 5.8. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ....................................69
Bҧng 5.9. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKÿѫQ cho fold 1 ....................................70
Bҧng 5.10. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ..................................70
Bҧng 5.11. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKÿѫQ cho fold 1 ..................................70
Bҧng 5.12. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKÿѫQ cho fold 1 ..................................71
Bҧng 5.13. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQK ÿѫQ cho fold 1 ..................................71
Bҧng 5.14. KӃt quҧ tәng hӧp các chӍ sӕ ÿiQKJLiÿӕi vӟLP{KuQKÿѫQ ............................71
Bҧng 5.15. Mô hình kӃt hӧp ..............................................................................................75
Bҧng 5.16. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 1 ............................76
Bҧng 5.17. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 2 ............................77
Bҧng 5.18. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 3 ............................77
Bҧng 5.19. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 4 ............................77
Bҧng 5.20. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 5 ............................78
Bҧng 5.21. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 6 ............................78
Bҧng 5.22. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 7 ............................78
Bҧng 5.23. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 8 ............................78
Bҧng 5.24. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 9 ............................79
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Bҧng 5.26. KӃt quҧ các thông sӕ ÿiQKJLiP{KuQKNӃt hӧp cho fold 1 ............................79
Bҧng 5.27. Bҧng so sánh các chӍ sӕ ÿiQKJLiP{KuQKÿѫQYjNӃt hӧp .............................80
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