ĈҤ,+Ӑ&48Ӕ&*,$73+&0
75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$
ĈӚ0,1++Ҧ,
3+Ӕ,+Ӧ37Ӕ,Ѭ85Ѫ-/(6Ӕ%Ҧ29ӊ48È'Ñ1*
&ÏĈӎ1++ѬӞ1*
&KX\rQQJjQK.ӻ7KXұWĈiӋQ
Mã Vӕ 8520201
/8Ұ19Ă17+Ҥ&6Ƭ
73+Ӗ&+Ë0,1+WKiQJ QăP
iii
&Ð1*75Î1+ĈѬӦ&+2¬17+¬1+7Ҥ,
75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$- Ĉ+4*- HCM
&iQEӝKѭӟQJGүQNKRDKӑF76+8ǣ1+48$1*0,1+
&iQEӝFKҩPQKұQ[pW 3*6763KҥPĈuQK$QK.K{L
&iQEӝFKҩPQKұQ[pW 76+XǤQK9ăQ9ҥQ
/XұQYăQWKҥFVƭÿѭӧFEҧRYӋWҥL7UѭӡQJĈҥLKӑF%iFK.KRD
TP.HCMĈҥLKӑF4XӕFJLD7S+&0QJj\WKiQJQăP
2021. (Online trên Google Meet)
7KjQKSKҫQ+ӝLÿӗQJÿiQKJLiOXұQYăQWKҥFVƭJӗP
1. TS. /r.ӹ
- &KӫWӏFK
2. TS. /r7Kӏ7ӏQK0LQK
- 7KѭNê
3. PGS.TS. 3KҥPĈuQK$QK.K{L
- 3KҧQELӋQ
4. TS. +XǤQK9ăQ9ҥQ
- 3KҧQELӋQ
5. TS. 7UҫQ+XǤQK1JӑF
- Ӫ\YLrQ
;iFQKұQFӫD&KӫWӏFK+ӝLÿӗQJÿiQKJLi/9Yj7UѭӣQJ.KRDTXҧQOê
FKX\rQQJjQKVDXNKLOXұQYăQÿmÿѭӧFVӱDFKӳDQӃXFy)
&+Ӫ7ӎ&+ +Ӝ, ĈӖ1*
75ѬӢ1*.+2$Ĉ,ӊ1-Ĉ,ӊ1 7Ӱ
iv
ĈҤ,+Ӑ&48Ӕ&*,$73+&0
75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$
&Ӝ1*+Ñ$;+Ӝ,&+Ӫ1*+Ƭ$9,ӊ71$0
ĈӝFOұS- 7ӵGR- +ҥQKSK~F
1+,ӊ0 9Ө/8Ұ19Ă17+Ҥ&6Ƭ
+ӑWrQKӑFYLrQĈӚ0,1++Ҧ,............................................. MSHV:1970040
1Jj\WKiQJQăP sinh: 20/12/1996.......................................... 1ѫLVLQKCà Mau
&KX\rQQJjQK.ӻ WKXұW ÿLӋQ .................................................. 0mVӕ 8520201
I. 7Ç1Ĉӄ7¬,³3+Ӕ,+Ӧ37Ӕ,Ѭ85Ѫ-/(6Ӕ%Ҧ29ӊ48È'Ñ1*
&ÏĈӎ1++ѬӞ1*´.
II. 1+,ӊ09Ө9¬1Ӝ,'81* :
x Tìm KLӇXWәQJTXDQYӅEjLWRiQWӕLѭXYjFiFKJLҧLEjLWRiQWӕLѭX.
x 7uPKLӇXYӅWӕLѭXKyDWURQJKӋWKӕQJÿLӋQYjPӝWVӕWKXұWWRiQWӕLѭX
WURQJKӋWKӕQJÿLӋQ.
x 7uPKLӇXWKXұWWRiQWӕLѭXFiYRL:2$YjUѫ-OHEҧRYӋTXiGzQJFy
KѭӟQJ.
x ӬQJGөQJWKXұWWRiQ:2$WURQJWӕLѭXKyDEҧRYӋUѫ-OHVӕFyÿӏQK
KѭӟQJ.
III. 1*¬<*,$21+,ӊ09Ө:22/02/2021
IV. 1*¬<+2¬17+¬1+1+,ӊ09Ө:13 /06/2021
V.
&È1%Ӝ+ѬӞ1*'Ү1: TS +8ǣ1+48$1*0,1+
Tp. HCM, ngày . . . . tháng ...... QăP 2021
&È1%Ӝ+ѬӞ1*'Ү1
&+Ӫ1+,ӊ0%Ӝ0Ð1Ĉ¬27Ҥ2
+XǤQK4XDQJMinh
75ѬӢ1*.+2$Ĉ,ӊ1- Ĉ,ӊ17Ӱ
v
/Ӡ,&Ҧ0Ѫ1
DE
/ӡL ÿҫX tiên, tôi xin chân thành FҧP ѫQ Vӵ quan tâm, giúp ÿӥ FӫD 7UѭӡQJ
ĈҥL KӑF Bách Khoa TP +ӗ Chí Minh, khoa ĈLӋQ - ĈLӋQ Wӱ và Eӝ môn +Ӌ WKӕQJ
ÿLӋQÿmKӛWUӧYjWҥRÿLӅXNLӋQWӕWQKҩWFKR W{LKRjQWKjQKNKyDKӑFWKҥFVƭYj
KRjQWKjQKOXұQ YăQ
7{LFNJQJ[LQFKkQWKjQKFҧPѫQTXê7Kҫ\&{FӫD.KRDĈLӋQ- ĈLӋQ7ӱ
ÿmWұQWuQKJLҧQJGҥ\W{LWURQJVXӕWWKӡLJLDQNKyDKӑFĈһFELӋWOjFiFWKҫ\F{
ӣ Eӝ môn +Ӌ WKӕQJ ÿLӋQ ÿm WұQ tâm KѭӟQJ GүQ WUX\Ӆn ÿҥW giúp tôi Eә sung thêm
QKLӅXNLӃQWKӭFFKX\rQQJjQKSKөFYөFKROXұQYăQFNJQJQKѭWURQJF{QJ YLӋF
KLӋQWҥLYjVDX này.
Và OӡL FҧP ѫQ sâu VҳF QKҩW [LQJӣL ÿӃQ TS +XǤQK4XDQJ0LQK ÿmÿӏQK
KѭӟQJÿӅWjLKѭӟQJGүQJLҧLTX\ӃWFiFYҩQ ÿӅYjWҥRPӑLÿLӅXNLӋQWKXұQOӧL
QKҩWWURQJTXiWUuQKW{LWKӵFKLӋQOXұQ YăQ
&XӕLFQJW{L[LQFiPѫQ7UXQJWkPĈLӅXÿӝ+ӋWKӕQJÿLӋQ73+ӗ&Kt
0LQKÿmWҥRÿLӅXNLӋQWKXұQOӧLFKRW{LWuPKLӇXYjFXQJFҩSGӳOLӋXJL~SKRjQ
WKjQKOXұQYăQQj\
Xin chân WKjQKFiPѫQ
7S+ӗ&Kt0LQKQJj\ «tháng «QăP
Ĉӛ0LQK+ҧL
vi
7Ï07Ҳ7/8Ұ19Ă1
DE
3+Ӕ,+Ӧ37Ӕ,Ѭ85Ѫ-/(6Ӕ%Ҧ29ӊ48È'Ñ1*&ÏĈӎ1++ѬӞ1*
/XұQYăQQj\WUuQKEj\YӅ FiFWKXұWWRiQWӕLѭXQyLFKXQJFNJQJQKѭWKXұWWRiQ
WӕL ѭXFiYRL:2$QyLULrQJYjӭQJGөQJFӫDFK~QJWURQJKӋWKӕQJÿLӋQ%rQFҥQK
ÿyOXұQYăQFNJQJWuPKLӇXYӅKӋWKӕQJEҧR YӋUѫ-OHÿһFELӋWOjUѫ-OHEҧRYӋTXi
GzQJFyÿӏQKKѭӟQJ7ӯÿyiSGөQJWKXұWWRiQWӕLѭXFiYRL:2$YjRYLӋFWtQK
WRiQSKӕLKӧSWӕLѭXKyDWKӡLJLDQEҧRYӋFӫDKӋWKӕQJUѫ-OHEҧRYӋTXiGzQJFy
ÿӏQKKѭӟQJÿӕLYӟLOѭӟL,(((EXVYjEXVÈSGөQJWKӵFWӃYjROѭӟLÿLӋQWUXQJ
WKӃN9FӫD+ӋWKӕQJÿLӋQ73+ӗ&Kt0LQK
ABSTRACT
DE
OPTIMIZATION CO-ORDINATION DIRECTIONAL OVERCURRENT RELAY
This thesis presents the optimization algorithms in general and whale
optimization algorithm (WOA) in specific as well as their applications in power
system. In additon, it also gets access to the relay protection system, particularly the
directional overcurrent relay. Since, we can put the WOA into practice calculating
optimization co-ordination directional overcurrent relay in the IEEE 3-bus and 8-bus
system. From that, the result will be applied into the 22kV power system of Ho Chi
Minh city.
vii
/Ӡ,&$0Ĉ2$1
DE
/XұQYăQWKҥFVƭQj\ÿѭӧFWKӵFKLӋQWҥL7UѭӡQJĈҥL+ӑF%iFK.KRD7S
+ӗ&Kt0LQK/jF{QJWUuQKGRW{LQJKLrQFӭXWKӵFKLӋQGѭӟLVӵKѭӟQJGүQWUӵF
WLӃSFӫD76. +XǤQK4Xang Minh.
7{L [LQ FDP ÿRDQ SKҫQ WUuQK Ej\ GѭӟL ÿk\ Oj ÿ~QJ Vӵ WKұW YӅ TXi WUuQK
QJKLrQFӭXWKӵFKLӋQOXұQYăQFӫDW{L7UѭӡQJKӧSFyNKLӃXQҥLJuOLrQTXDQWӟL
OXұQYăQW{LKRjQWRjQFKӏXWUiFKQKLӋP VLӋFWKDPNKҧRFiFQJXӗQWjLOLӋXÿm
ÿѭӧFWKӵFKLӋQWUtFKGүQYjJKLQJXӗQWjLOLӋXWKDPNKҧRÿ~QJTX\ÿӏQK
7S+͛&Kt0LQKQJj\«WKiQJ«QăP
+ӑFYLrQ
Ĉӛ0LQK+ҧL
MӨC LӨC
MӢ ĈҪU .......................................................................................................................... 1
1.
Ĉһt vҩQÿӅ ..................................................................................................................... 1
2.
0өFWLrXFӫDOXұQYăQ................................................................................................... 1
3.
3KѭѫQJSKiSWKӵFKLӋQ ................................................................................................ 2
4.
ĈӕLWѭӧQJYjSKҥPYLQJKLrQFӭX ................................................................................ 2
5.
éQJKƭDWKӵF WLӉQFӫDÿӅWjL .......................................................................................... 2
&+ѬѪ1*7ӘNG QUAN Vӄ BÀI TOÁN TӔ,Ѭ8 .................................................. 3
1.1.
%jLWRiQWӕLѭX............................................................................................................... 3
1.2.
&iFORҥLEjLWRiQWӕLѭX ................................................................................................. 4
1.3.
3KѭѫQJSKiSWӕLѭX ...................................................................................................... 6
&+ѬѪ1*7Ӕ,Ѭ8+Ï$7521*+ӊ THӔ1*Ĉ,ӊN ............................................ 9
2.1.
.KiLQLӋP ...................................................................................................................... 9
2.2.
&iFSKѭѫQJSKiSWӕLѭXKyDWURQJKӋWKӕQJÿLӋQ ......................................................10
2.3. *LӟLWKLӋXPӝWVӕSKѭѫQJSKiSWuPNLӃPWӕLѭX+HXULVWLFVÿѭӧFVӱGөQJWURQJKӋ
WKӕQJÿLӋQ ...............................................................................................................................11
&+ѬѪ1*: THUҰT TOÁN TӔ,Ѭ8&È92,:2$ ............................................ 29
3.1.
&iFEѭӟc thӵc hiӋn thuұt toán tӕLѭXWOA ...............................................................29
3.2.
/ѭXÿӗ giҧi thuұt cӫa thuұt toán tӕLѭX:2$ ..........................................................33
&+ѬѪ1**,ӞI THIӊU Vӄ 5Ѫ-LE BҦO Vӊ 48È'Ñ1*&Ï+ѬӞNG. ......... 35
4.1.
Giӟi thiӋu chung vӅ 5ѫ-le bҧo vӋ.................................................................................35
4.2.
Nguyên lý bҧo vӋ TXiGzQJÿLӋQTXiGzQJÿLӋn có Kѭӟng .........................................39
&+ѬѪ1* ӬNG DӨNG THUҰT TOÁN WOA TRONG TӔ, Ѭ8 +Ï$ %ҦO Vӊ
5Ѫ-LE SӔ &ÏĈӎ1++ѬӞNG. ................................................................................... 54
5.1.
Ĉһc tuyӃQGzQJÿLӋn - thӡi gian cӫDUѫ-OHTXiGzQJÿӏQKKѭӟng ...............................54
5.2.
Hàm mөc tiêu và các ràng buӝc ..................................................................................55
5.3.
Áp dөng thuұt toán GWO tính toán phӕi hӧp bҧo vӋ Uѫ-le FKROѭӟi IEEE chuҭn.....56
5.4.
Áp dөng thuұWWRiQ:2$ÿӇ WtQKWRiQFKROѭӟLÿLӋn Thành phӕ Hӗ Chí Minh .......68
&+ѬѪ1*.ӂT LUҰ19¬ĈӎNH +ѬӞNG NGHIÊN CӬ87521*7ѬѪ1*/$,
........................................................................................................................................ 73
6.1.
KӃt luұn ........................................................................................................................73
6.2.
ĈӏQKKѭӟng nghiên cӭXWURQJWѭѫQJODL ......................................................................74
TÀI LIӊU THAM KHҦO ............................................................................................. 76
LÝ LӎCH TRÍCH NGANG ........................................................................................... 78
DANH MӨC HÌNH ҦNH
+uQK&iFEѭӟc thӵc hiӋn thuұt toán di truyӅn ....................................................... 16
Hình 2.2 Các thành phҫn và mӕi liên hӋ giӳa chúng cӫa thuұt toán di truyӅn ........... 16
Hình 2.3 Minh hӑa quá trình thích nghi vӟi hoàn cҧnh sӕng cӫDEѭѫPEѭӟm .......... 17
+uQK/ѭXÿӗ giҧi thuұt cӫa thuұt toán di truyӅn ................................................... 18
Hình 2.5 HӋ thӕng phân cҩp thӕng trӏ xã hӝi trong bҫy sói xám ................................. 19
+uQK4XiWUuQKVăQPӗi cӫa sói xám ....................................................................... 21
Hình 2.7 Vec-Wѫ vӏ trí trong 2D và 3D ........................................................................... 22
Hình 2.8 Cұp nhұt vӏ trí trong GWO ............................................................................ 23
Hình 3.1 Vӏ trí tӕLѭXWURQJNK{QJJLDQ'................................................................... 30
Hình 3.2 Vӏ trí tӕLѭXWURQJNK{QJJLDQD................................................................... 31
Hình 3.3 Cұp nhұt vӏ trí theo hình xoҳn ӕc................................................................... 31
+uQK&ѫFKӃ WKăPGzÿѭӧc thӵc hiӋn trong thuұt toán WOA ............................... 32
Hình 4.1 Nguyên nhân gây sӵ cӕ trong hӋ thӕQJÿLӋn .................................................. 35
Hình 4.2 Tính chӑn lӑc cӫa bҧo vӋ UѫOH........................................................................ 38
+uQKĈѭӡng dây hình tia mӝt nguӗn ...................................................................... 40
+uQKĈһc tính thӡLJLDQÿӝc lұp và phө thuӝc ........................................................ 41
Hình Ĉӗ thӏ tính toán bҧo vӋ quá dòng cҳt nhanh không thӡi gian ....................... 44
+uQK6ѫÿӗ OѭӟLÿLӋn vӟi bҧo vӋ quá dòng cҳt nhanh ............................................. 44
Hình 4.7 Các bҧo vӋ TXiGzQJÿLӋn pha ....................................................................... 45
Hình 4.8 Phҥm vi bҧo vӋ cӫa quá dòng cҳt nhanh ....................................................... 46
+uQK6ѫÿӗ OѭӟLÿLӋn phӭc tҥp yêu cҫu bҧo vӋ FyKѭӟng ....................................... 48
Hình 4.10 DònJÿLӋQYjÿLӋn áp tham chiӃu cӫa bӝ phұQÿӏQKKѭӟng công suҩt........ 49
+uQKĈһc tính hoҥWÿӝng cӫa phҫn tӱ ÿӏnKKѭӟng ............................................... 50
+uQK6ѫÿӗ hӋ thӕQJÿLӋn 3 nút ............................................................................... 58
+uQK6ѫÿӗ hӋ thӕQJÿLӋn 8 nút ............................................................................... 63
Hình 5.3 Thông sӕ tuyӃn dây 473 Tân Xuân ................................................................ 69
+uQK6ѫÿӗ tuyӃn 473 Tân Xuân vӁ bҵng Etap....................................................... 70
Hình 5.5 PhiӃu chӍQKÿӏQKUѫ-OHGR7UXQJWkPĈLӅXÿӝ HӋ thӕQJÿLӋn miӅn Nam ban
hành««««««««««««««««««««««««««««««««« 71
'$1+0Ө&%Ҧ1*%,ӆ8
Bҧng 5.1 Chuҭn IEEE cho các loҥLÿһc tuyӃn khác nhau ............................................ 55
Bҧng 5.2 Dӳ liӋu máy phát cho hӋ thӕng 3 nút ............................................................. 58
Bҧng 5.3 Dӳ liӋXÿѭӡng dây cho hӋ thӕng 3 nút ........................................................... 58
Bҧng 5.4 Tӹ sӕ biӃn dòng cӫa các CT cho hӋ thӕng 3 nút ............................................ 59
BҧQJ'zQJÿLӋn sӵ cӕ và dӵ phòng khi sӵ cӕ xҧy ra cho hӋ thӕng 3 nút ............... 59
Bҧng 5.6 Thӡi gian vұn hành cӫa tӯQJUѫOHYjUjQJEXӝFWѭѫQJӭng ........................ 60
Bҧng 5.7 So sánh kӃt quҧ cho hӋ thӕng 3 nút ............................................................... 60
Bҧng 5.8 Thӡi gian vұn hành cӫa tӯQJUѫOHYjUjQJEXӝFWѭѫQJӭng ........................ 61
Bҧng 5.9 So sánh kӃt quҧ cho hӋ thӕng 3 nút ............................................................... 62
Bҧng 5.10 Dӳ liӋu máy phát cho hӋ thӕng 8 nút ........................................................... 63
Bҧng 5.11 Dӳ liӋXÿѭӡng dây cho hӋ thӕng 8 nút ......................................................... 63
Bҧng 5.12 Tӹ sӕ CT cho hӋ thӕng 8 nút ........................................................................ 64
Bҧng 5.13 Dòng sӵ cӕ và dӵ phòng khi sӵ cӕ xҧy ra cho hӋ thӕng 8 nút ..................... 64
Bҧng 5.14 Thӡi gian vұn hành cӫa tӯQJUѫOHYjÿLӅu kiӋn ràng buӝFWѭѫQJӭng ...... 66
BҧQJ6RViQKSKѭѫQJSKiS:2$YӟLFiFSKѭѫQJSKiSNKiF ............................ 66
Bҧng 5.16 Thӡi gian vұn hành cӫa tӯQJUѫOHYjÿLӅu kiӋn ràng buӝFWѭѫQJӭng vӟLÿһc
tuyӃn Very Inverse......................................................................................................... 67
Bҧng 5.17 So sánh vӟLFiFSKѭѫQJSKiSNKiF ............................................................ 667
Bҧng 5.18 Các sӕ liӋu dùng cho viӋc tính toán phӕi hӧp thӡi gian cho tuyӃn Tân Xuân
........................................................................................................................................ 70
Bҧng 5.19 KӃt quҧ phӕi hӧp bҧo vӋ UѫOHFKRWX\Ӄn 473 Tân Xuân ............................. 72
1
MӢ ĈҪU
1. Ĉһt vҩQÿӅ
7URQJQKӳQJQăPJҫQÿk\WӕLѭXKyDÿmWUӣQrQSKәELӃQYjÿѭӧFӭQJ
GөQJUӝQJUmLWURQJFiFOƭQKYӵFQJKLrQFӭXNKiFQKDX7ӕLѭXKyDYjSKѭѫQJ
SKiSWӕLѭXÿmÿѭӧFSKiWWULӇQUҩW PҥQKWURQJ QKӳQJ QăP JҫQÿk\ÿӇ JLҧL
TX\ӃWQKӳQJEjLWRiQOӟQYjSKӭFWҥSWURQJWKӵFWLӉQ7KHR[XKѭӟQJSKiW
WULӇQFӫDFiFSKѭѫQJSKiSWӕLѭXJҫQÿk\FiFSKѭѫQJSKiSWK{QJPLQKQKkQ
WҥRÿѭӧFSKiWWULӇQUҩWQKDQKÿӇJLҧLTX\ӃWQKӳQJEjLWRiQ PjFiFSKѭѫQJ
SKiSFәÿLӇQNK{QJWKӇJLҧLTX\ӃWÿѭӧF0ӝWWURQJQKӳQJѭXÿLӇPFӫDFiF
SKѭѫQJSKiSWK{QJPLQKQKkQWҥROjFyWKӇJLҧLTX\ӃWÿѭӧFQKӳQJEjLWRiQ
SKӭFWҥSPjNK{QJÿzLKӓLGҥQJWRiQKӑFFKXҭQOLQKÿӝQJWURQJӭQJGөQJ
YjRFiFEjLWRiQNKiFQKDXYjGӉGjQJNӃWKӧSYӟLFiFSKѭѫQJSKiSNKiFÿӇ
WҥRWKjQKSKѭѫQJSKiSKLӋXTXҧKѫQ
1Jj\QD\WURQJOƭQKYӵFNӻWKXұWÿLӋQYLӋFVҧQ[XҩWWUX\ӅQWҧLÿLӋQQăQJ
SKҧL WUҧLTXDQKLӅXNKkXQKLӅXJLDLÿRҥQSKӭFWҥSQrQNK{QJWKӇWUiQKNKӓL
QKӳQJVӵFӕKѭKӓQJ'RÿyÿӇGX\WUuVӵOjPYLӋFOLrQWөFәQÿӏQKFKRKӋ
WKӕQJVҧQ[XҩWWUX\ӅQWҧLWLrXWKөÿLӋQQăQJFNJQJQKѭQkQJFDRÿӝWLQFұ\
FXQJFҩSÿLӋQÿҧPEҧRDQWRjQFKRFRQQJѭӡLWKLӃWEӏ«WKuKӋWKӕQJUѫ-le
EҧRYӋPDQJWtQKVӕQJFzQFKRKӋWKӕQJÿLӋQ/XұQYăQQj\WUuQKEj\SKѭѫQJ
SKiSSKӕL KӧSUѫ-OHVӕEҧRYӋTXiGzQJFyÿӏQK KѭӟQJ'2&5FKR OѭӟL
ÿLӋQ WUXQJ WKӃ QKҵP F{ OұS QKDQK FKyQJ FiF SKҫQ Wӱ EҩW WKѭӡQJ WURQJ KӋ
WKӕQJÿҧPEҧRÿӝQKҥ\WtQKFKӑQOӑFÿӝWLQFұ\NKҧQăQJWiFÿӝQJQKDQK
FKyQJYjWtQKNLQKWӃFKRKӋWKӕQJÿLӋQ
2. 0өFWLrXFӫDOXұQYăQ
0өFWLrXFӫDOXұQYăQOjQJKLrQFӭX[iFÿӏQKWәQJWKӡLJLDQSKӕLKӧSFӫD
FiFUѫ-OHWURQJKӋWKӕQJOjQKӓQKҩWQKҵPWăQJFѭӡQJKLӋXTXҧKRҥWÿӝQJ
FӫDFK~QJ&өWKӇOj
- 7UuQKEj\FiFSKѭѫQJSKiSJLҧLEjLWRiQWӕLѭXWURQJKӋWKӕQJÿLӋQ
- 7UuQKEj\P{KuQKWRiQSKѭѫQJSKiSiSGөQJFKREjLWRiQSKӕLKӧS
EҧRYӋUѫ-le.
- 7tQKWRiQP{SKӓQJFKRKӋWKӕQJPүX
2
- ӬQJGөQJYjRPӝWSKiWWX\ӃQWKӵFWӃWURQJOѭӟLÿLӋQWUXQJWKӃ73+ӗ
Chí Minh.
3. 3KѭѫQJSKiSWKӵFKLӋQ
- ;k\GӵQJP{KuQKKӋWKӕQJÿLӋQSKkQSKӕLÿLӇQKuQKFyVӵWKkPQKұS
FӫDÿLӋQPһWWUӡLiSPiLQӕLOѭӟLKҥWKӃWKHRQKLӅXFҩSÿӝ
- 7tQKWRiQEӝWK{QJVӕWӕLѭXFKRYLӋFSKӕLKӧSEҧRYӋUѫ-le quá dòng
FyKѭӟQJ
- 6ӱGөQJSKҫQPӅP(WDS0DWODEÿӇP{SKӓQJÿiQKJLiNӃWTXҧ
4. ĈӕLWѭӧQJYjSKҥPYLQJKLrQFӭX
- ĈӕLWѭӧQJQJKLrQFӭXFӫDOXұQYăQOjFiFSKѭѫQJSKiSJLҧLEjLWRiQWӕL
ѭXFNJQJQKѭYLӋFiSGөQJEjLWRiQWӕLѭXYjRYLӋFSKӕLKӧSWtQKWRiQEҧR
YӋUѫ-le.
- 3KҥPYLQJKLrQFӭXOjOѭӟLÿLӋQSKkQSKӕLPүX,(((EXVFy[pWWӟL
KӋWKӕQJÿLӋQPһWWUӡLKzDOѭӟL
5. éQJKƭDWKӵFWLӉQFӫDÿӅWjL
- 1JKLrQFӭXFiFEjLWRiQWӕLѭXWURQJKӋWKӕQJÿLӋQWӯÿyJLҧLTX\ӃWEjL
WRiQSKӕLKӧSEҧRYӋUѫ-le.
- ĈӅ[XҩWJLҧLSKiSSKӕLKӧSEҧRYӋUѫ-OHSKөFYөFKRF{QJYLӋF
3
&+ѬѪ1*7Ә1*48$19ӄ%¬,72È17Ӕ,Ѭ8
1.1. %jLWRiQWӕLѭX
7ӕLѭXKRiOjPӝWWұSKӧSFiFSKѭѫQJSKiSWRiQKӑFÿѭӧFVӱGөQJÿӇJLҧL
FiFEjLWRiQÿӏQKOѭӧQJWURQJQKLӅXOƭQK YӵFQKѭYұWOêNӻWKXұWNLQKWӃ«
+ҫXKӃWFiFEjLWRiQWӕLѭXÿѭӧFWKjQKOұSWUrQFѫVӣWRiQKӑFYjÿѭӧFJLҧL
TX\ӃWWKHRFiFSKѭѫQJSKiSQKҩWÿӏQKÿӇÿҥWÿѭӧFOӡLJLҧLWӕLѭX9LӋFJLҧL
PӝWEjLWRiQWӕLѭXFKtQKOjWuPNLӃPOӡLJLҧLWӕWQKҩWWURQJWҩWFҧ FiFOӡLJLҧL
NKҧWKLFӫDEjLWRiQ
0ӝWEjLWRiQWӕLѭXEDRJӗPKjPPөFWLrXYjFiFELӃQUjQJEXӝFÿѭӧFELӇX
GLӉQGѭӟLGҥQJELӇXWKӭFWRiQKӑF&iFWKjQKSKҫQÿһWWUѭQJFӫDPӝWEjLWRiQ
WӕLѭXJӗPFy
- +jPPͭFWLrX)XQFWLRQ OjPөFÿtFKFӫDEjLWRiQWӕL ѭXÿѭӧFWKӇKLӋQ
GѭӟLFiFKjPVӕWRiQKӑF9tGөQKѭWӕLѭXSKkQEӕF{QJVXҩWWURQJKӋWKӕQJ
ÿLӋQFӵFWLӇXFKLSKtVҧQ[XҩWNKtFөÿLӋQSKӕLKӧSWӕLѭXEҧRYӋUѫ-OHVӕ«
+jPPөFWLrXWKѭӡQJÿѭӧFNêKLӋXOj)[YӟL[OjWұSKӧSFiFELӃQFӫDEjL
toán.
- %L͇QV͙9DULDEOHV OjFiFÿҥLOѭӧQJPjJLiWUӏFӫDQyÿѭӧF[iFÿӏQK
VDRFKRKjPPөFWLrXÿҥWWӕLѭXQKҩW9tGөJLiWUӏÿLӋQiSYjGzQJÿLӋQWURQJ
WUѭӡQJKӧSSKkQEӕF{QJVXҩWWӕLѭXWXәLWKӑYjNKҧQăQJYұQKjQKFӫDFiF
NKtFөÿLӋQWURQJWUѭӡQJKӧSWӕLWKLӇXKRiFKLSKtVҧQ[XҩWWӕLWKLӇXWKӡLJLDQ
WiFÿӝQJFӫDFiFUѫ-OHWURQJYLӋFSKӕLKӧSEҧRYӋUѫ-OH«7ұSFiFELӃQWKѭӡQJ
ÿѭӧFNêKLӋXOj[ [1, x2, x3«[nYӟL[i L QOjFiFELӃQWKjQK
SKҫQYjQOjNtFKFӥFӫDEjLWRiQ
- %L͇QUjQJEX͡F WKӇKLӋQPӕLTXDQKӋJLӳDFiFELӃQWKHRWtQKFKҩWFӫD
EjLWRiQFNJQJQKѭJLӟLKҥQJLiWUӏFӫDFiFELӃQFyWKӇQKұQÿѭӧF&yORҥL
UjQJEXӝFOjUjQJEX͡Fÿ̻QJWKͱF ÿѭӧFWKӇKLӋQGѭӟLGҥQJFiFSKѭѫQJWUuQK
và UjQJEX͡FḘWÿ̻QJWKͱF ÿѭӧFWKӇKLӋQGѭӟLGҥQJFiFEҩWSKѭѫQJWUuQK9t
GөQKѭFiFSKѭѫQJWUuQKFkQEҵQJF{QJVXҩWWURQJKӋWKӕQJÿLӋQOjFiFUjQJ
EXӝFÿҷQJWKӭFYjJLӟLKҥQWKӡLJLDQWiFÿӝQJFӫDFiFUѫ-OHOjFiFUjQJEXӝF
EҩWÿҷQJWKӭF&iFUjQJEXӝFÿҷQJWKӭFWKѭӡQJÿѭӧFNêKLӋXOjK[ và
FiFUjQJEXӝFEҩWÿҷQJWKӭFWKѭӡQJÿѭӧFNêKLӋXOjJ[
4
0{KuQKWәQJTXiWFӫDPӝWEjLWRiQWӕLѭX
Min F(x)
hi [ L «S
gj [M «N
YӟL[ >[1, x2«[n@OjWұSFiFELӃQFҫQ[iFÿӏQKWURQJEjLWRiQ
*LҧVӱEjLWRiQJӗPn ELӃQVӕYjm UjQJEXӝFÿLӅXNLӋQÿӇFyEjLWRiQWӕL
ѭXOj
- 1ӃXQPEjLWRiQWKXӝFORҥLTXiUjQJEXӝFYjNK{QJFyOӡLJLҧL
%jLWRiQQj\NK{QJWKXӝFORҥLEjLWRiQWӕLѭX
- 1ӃXQ PEjLWRiQQj\WKXӝFORҥL[iFÿӏQKYjFKӍFyPӝWWұSQJKLӋP
duy nKҩWNK{QJWKXӝFORҥLEjLWRiQWӕLѭX
- 1ӃXQ!PEjLWRiQWKXӝFORҥLWKLӃXUjQJEXӝFYjFyY{VӕQJKLӋP
FyQKLӅXNK{QJJLDQÿӇWuPNLӃPOӡLJLҧLWӕLѭX7URQJY{VӕQJKLӋP
VӁFyPӝWQJKLӋPOjPFKRKjPPөFWLrXÿҥWÿѭӧFJLiWUӏQKѭPRQJ
ÿӧL
0ӝWOӡLJLҧLFKREjLWRiQWӕLѭXÿѭӧFJӑLOjNKҧWKLQӃXOӡLJLҧLÿyWKӓDPmQ
WҩWFҧFiFUjQJEXӝFFӫDEҧLWRiQÿy'RÿyPӝWEjLWRiQWӕLѭXWKѭӡQJFy
QKLӅXOӡLJLҧLNKҧWKLNKiFQKDXWURQJVӕQKӳQJOӡLJLҧLÿyVӁFyPӝWOӡLJLҧL
WӕWQKҩWÿѭӧFJӑLOjOӡLJLҧLWRjQFөFYjQKӳQJOӡLJLҧLNKiFÿѭӧFJӑLOjOӡL
JLҧLFөFEӝ0өFÿtFKJLҧLPӝWEjLWRiQWӕLѭXOjWuPNLӃPOӡLJLҧLWRjQFөFWӯ
Y{VӕOӡLJLҧLFөFEӝ7X\QKLrQYLӋFWuPNLӃPOӡLJLҧLWRjQFөFOjPӝWWKiFK
WKӭFOӟQFKRFiFSKѭѫQJSKiSWӕLѭXiSGөQJFKRFiFEjL WRiQOӟQYӟLQKLӅX
UjQJEXӝFSKӭFWҥS&KtQKYuYұ\PjFiFSKѭѫQJSKiSWӕLѭXOX{QÿѭӧFSKiW
WULӇQÿӇiSGөQJFKRFiFEjLWRiQOӟQYjSKӭFWҥSWURQJWKӵFWLӉQ
9LӋFJLҧLEjLWRiQWӕLѭXWKѭӡQJÿѭӧFTX\YӅJLҧLEjLWRiQFӵFWLӇX1ӃXFҫQ
WuPJLiWUӏWӕLѭX FӵFÿҥL0D[)[QJѭӡLWDWKѭӡQJTX\YӅEjLWRiQFӵFWLӇX
là Min ±)[KRһF0LQ)[
1.2. &iFORҥLEjLWRiQWӕLѭX
&iFEjLWRiQWӕLѭXWKѭӡQJÿѭӧFSKkQORҥLWKHRELӃQWKHRELӇXWKӭFWRiQ
WKHRUjQJEXӝFKRһFWKHRKjPPөFWLrX
5
3KkQOR̩LWKHREL͇Q
x 7ӕLѭXKyDOLrQWөFQӃXEjLWRiQFKӍFyFKӭDFiFELӃQWKӵFOLrQWөF
WKuÿѭӧFJӑLOjEjLWRiQWӕLѭXOLrQWөFÿѭӧFQJKLrQFӭXSKәELӃQ
QKҩWKLӋQQD\
x 7ӕLѭXKyDUӡLUҥFQӃXEjLWRiQFyFKӭDFҧFiFELӃQWKӵFOLrQWөF
YjFiFELӃQUӡLUҥFWKuÿѭӧFJӑLOjEjLWRiQWӕLѭXUӡLUҥFKD\EjL
WRiQWӕLѭXWәKӧSJk\NKyNKăQFKRYLӋFWuPNLӃPOӡLJLҧL
3KkQOR̩LWKHRE̫QFK̭WEL͋XWKͱFWRiQ
x 7ӕLѭXKyDWX\ӃQWtQKQӃXEjLWRiQJӗPFyFҧKjPPөFWLrXYj
FiFUjQJEXӝFÿӅXOjKjPWX\ӃQWtQKWKuÿk\OjEjLWRiQWӕLѭXWX\Ӄn
tính.
x 7ӕLѭXKyDSKLWX\ӃQQӃXEjLWRiQFytWQKҩWPӝWELӇXWKӭFWRiQ
KӑFSKLWX\ӃQWURQJKjPPөFWLrXKRһFFiFUjQJEXӝFWKuÿk\Oj
EjLWRiQWӕLѭXKyDSKLWX\ӃQ7URQJEjLWRiQWӕLѭXKyDSKLWX\ӃQ
FzQFKLDUDSKLWX\ӃQNKҧYLYjSKLWX\ӃQNK{QJNKҧvi.
3KkQOR̩LWKHRWtQKFK̭WFͯDEL͇Q
x 7ӕLѭXKyD[iFÿӏQKWURQJEjLWRiQWӕLѭX[iFÿӏQKNӃWTXҧWӕLѭX
WRjQFөFÿҫXUDVӁOX{QOX{QJLӕQJQKDXQӃXÿҫXYjRJLӕQJQKDX
7URQJORҥLEjLWRiQQj\WKuWҩWFҧFiFELӃQOj[iFÿӏQK
x 7ӕLѭXKyDQJүXQKLrQWURQJEjLWRiQQj\PӝWVӕKRһFWҩWFҧFiF
ELӃQÿѭӧFELӇXGLӉQGѭӟLGҥQJ[iFVXҩW
3KkQOR̩LWKHRUjQJEX͡F
x 7ӕLѭXKyDNK{QJFyUjQJEXӝFEjLWRiQWӕLѭXFKӍFyKjPPөF
WLrXYjNK{QJFyUjQJEXӝF&iFEjLWRiQWӕLѭXGҥQJQj\WKѭӡQJ
GQJÿӇWuPNLӃPFiFSKѭѫQJSKiSWӕLѭXPӟLQKѭQJNK{QJFyJLi
WUӏWKӵFWLӉQ
x 7ӕLѭXKyDFyUjQJEXӝFEjLWRiQWӕLѭXJӗPKjPPөFWLrXYjFiF
UjQJEXӝFÿҷQJWKӭFEҩWÿҷQJWKӭFÿѭӧFӭQJGөQJSKәELӃQWURQJ
FiFOƭQKYӵFFӫDWKӵFWLӉQ
3KkQOR̩LWKHRV͙O˱ͫQJKjPPͭFWLrX
x 7ӕLѭX KyDÿѫQPөFWLrXQӃXEjLWRiQWӕLѭXFyPӝWKjPPөFWLrX
WKuÿѭӧFJӑLOjEjLWRiQWӕLѭXÿѫQPөFWLrXSKѭѫQJWKӭFJLҧLOj
6
WuPUDOӡLJLҧLOjPFKRKjPPөFWLrXÿҥWJLiWUӏOӟQQKҩWKRһFQKӓ
QKҩWWURQJY{VӕOӡLJLҧLNKҧWKL
x 7ӕLѭXKyDÿDPөFWLrXQӃXEjLWRiQWӕLѭXFyWӯKjPPөFWLrX
WUӣOrQWKuÿѭӧFJӑLOjEjLWRiQWӕLѭXÿDPөFWLrX%jLWRiQQj\
NKiFYӟLEjLWRiQÿѫQPөFWLrXOjFiFPөFWLrXELӃQWKLrQQJѭӧF
QKDXWӭFOjQӃXWұSWUXQJYjRPӝWPөFWLrXWKuFiFPөFWLrXNKiF
VӁNK{QJWӕW'RÿySKѭѫQJSKiSJLҧLOjFҫQWuPÿѭӧFOӡLJLҧLWKӓD
KLӋSPөFWLrXWӕLѭXWӭFOjYӅPһWFiWKӇVӁNK{QJFyKjP PөF
WLrXQjRWӕWQKҩWQKѭQJYӅPһWWәQJWKӇWKuOjWӕWQKҩW
1.3. 3KѭѫQJSKiSWӕLѭX
&iFSKѭѫQJSKiSWӕLѭXÿѭӧFGQJÿӇJLҧLFiFEjLWRiQWӕLѭXNKiFQKDX
ÿѭӧFWKjQKOұSGѭӟLGҥQJWRiQKӑF0өFWLrXFӫDFiFSKѭѫQJSKiSQj\OjWuP
UDOӡLJLҧLWӕLѭXKRһFJҫQWӕLѭXFKRFiFEjLWRiQYӟLNKҧQăQJWtQKWRiQFjQJ
tWFjQJWӕW.KҧQăQJWtQKWRiQFӫDPӝWSKѭѫQJSKiSWӕLѭXWKѭӡQJÿѭӧFWKӇ
KLӋQTXDEӝQKӟ Pm\WtQKÿѭӧFVӱGөQJ YjWKӡLJLDQWtQKWRiQFӫDSKѭѫQJ
SKiS7X\QKLrQÿӕLYӟLQKLӅXSKѭѫQJSKiSPjQKҩWOjFiFSKѭѫQJSKiSWuP
NLӃPWKuFyVӵÿiQKÿәLJLӳDFKҩWOѭӧQJOӡLJLҧLYjWKӡLJLDQWtQKWRiQQӃX
WKӡLJLDQWtQKWRiQFjQJOkXWKuFKҩWOѭӧQJOӡLJLҧLFjQJFDRYjQJѭӧFOҥL
+LӋQQD\FyKDLORҥLSKѭѫQJSKiSWӕLѭXOjFiFSKѭѫQJSKiSWӕLѭXFKtQK
[iFKD\FzQJӑLOjSKѭѫQJSKiSFәÿLӇQYjFiFSKѭѫQJSKiSWӕLѭXWuPNLӃP
JҫQÿ~QJ
1.3.1. 3K˱˯QJSKiSW͙L˱XF͝ÿL͋Q
3KѭѫQJSKiSWӕLѭXFәÿLӇQUҩWKLӋXTXҧWURQJYLӋFWuP UDOӡLJLҧLFKRFiF
EjLWRiQWӕLѭXOLrQWөFYjNKҧYL&ѫVӣFKtQKFӫDFiFSKѭѫQJSKiSFәÿLӇQOj
GӵDWUrQYLSKkQÿӇÿӏQKKѭӟQJÿLӇPWӕLѭX'RÿyFiFSKѭѫQJSKiSFәÿLӇQ
EӏKҥQFKӃiSGөQJYjRFiFEjLWRiQWKӵFWLӉQQӃXFiFEjLWRiQQj\FyFKӭDFiF
hàPNK{QJOLrQWөFYjNK{QJNKҧYL+ѫQQӳDSKѭѫQJSKiSWӕLѭXFәÿLӇQ
WKѭӡQJKD\JһSPӝWYҩQÿӅQӳDOjNKLNtFKFӥEjLWRiQWăQJOrQWKuWKӡLJLDQ
JLҧLEjLWRiQVӁWăQJOrQWKHRGҥQJKjPPNJFӫDNtFKWKѭӟFEjLWRiQ7X\QKLrQ
YLӋFQJKLrQFӭXFiFSKѭѫQJSKiSFәÿLӇQWҥRWKjQKFѫVӣÿӇSKiWWULӇQKҫXKӃW
FiFSKѭѫQJSKiSVӕOLrQTXDQÿӇPӣUӝQJUDFiFSKѭѫQJSKiSKLӋQÿҥLSK
KӧSYӟLFiFEjLWRiQWKӵFWLӉQKѫQ
7
ĈӇJLҧLFiFEjLWRiQWӕLѭXEҵQJSKѭѫQJSKiSFәÿLӇQWKuFҫQFyÿLӅXNLӋQ
UҵQJFiFKjPWURQJEjLWRiQFyÿҥRKjPEұFKDLWKHRFiFELӃQYjFiFÿҥRKjP
Qj\OLrQWөFFiFSKѭѫQJSKiSWӕLѭXWKXӝFQKyPFәÿLӇQÿѭӧFVӱGөQJSKә
ELӃQ QKѭ 4X\ KRҥFK WX\ӃQ WtQK 4X\ KRҥFK WRjQ SKѭѫQJ 3KѭѫQJ SKiS
/DJUDQJH3KѭѫQJSKiSOһS1HZWRQ± 5DOSVRQ«
1.3.2. 3K˱˯QJSKiSWuPNL͇P
CáFSKѭѫQJSKiSWuPNLӃPNKiFYӟLFiFSKѭѫQJSKiSFәÿLӇQOjOX{QEҧR
ÿҧPWuPÿѭӧFOӡLJLҧLYjWKѭӡQJWuPNLӃPFiFOӡLJLҧLJҫQWӕLѭX7X\QKLrQ
FiFSKѭѫQJSKiSWuPNLӃPFyWKӇWLӃSFұQFiFEjLWRiQWӕLѭXNKiFQKDXPj
FiFSKѭѫQJSKiSFәÿLӇQNK{QJWKӇJLҧLTX\ӃWÿѭӧFNKLFiFEjLWRiQ[HP[pW
NK{QJFҫQFyWtQKNKҧYLKD\NK{QJ1JX\rQOêFӫDFiFSKѭѫQJSKiSQj\Oj
GӵDWUrQVӕFiWKӇÿӇWuPNLӃPOӡLJLҧLWӕLѭXGӵDWUrQVӵWKD\ÿәLQJүXQKLrQ
WURQJNK{QJJLDQEjLWRiQYjVRViQKÿӇWuPUDOӡLJLҧLWӕWQKҩW &iFSKѭѫQJ
SKiSQj\GӉiSGөQJYjNK{QJFҫQNLӃQWKӭFÿһFELӋWYӅWӕLѭXKyDÿӇJLҧLEjL
WRiQWӕLѭX1KѭӧFÿLӇPFӫDFiFSKѭѫQJSKiSWuPNLӃPFKtQKOjSKҧLOӵDFKӑQ
FiFWK{QJVӕWKtFKKӧSFKRSKѭѫQJSKiSYjWKӵFKLӋQQKLӅXOҫQFKҥ\ÿӝFOұS
ÿӇWuPUDOӡLJLҧLWӕWQKҩWPjFiFWK{QJVӕSKҧLÿѭӧFWuPNLӃPEҵQJFiFKWKӱ
QJKLӋPFKRWӯQJEjLWRiQNKiFQKDX1ӃXEjLWRiQWӕLѭXFjQJOӟQWKuYLӋFiS
GөQJFiFSKѭѫQJSKiSWUӣQrQNKyNKăQKѫQYjPҩWQKLӅXWKӡLJLDQKѫQGR
SKҧLGQJQKLӅXFiWKӇWURQJTXҫQWKӇÿӇWKӵFKLӋQQKLӅXOҫQFKҥ\ÿӝFOұS
&iFSKѭѫQJSKiSWuPNLӃPFyWKӇSKkQFҩSQKѭVDX
- &iFSK˱˯QJSKiSWuPNL͇PWKHRTX\W̷FKHXULVWLF &iFSKѭѫQJSKiS
Qj\WKѭӡQJJҳQOLӅQYӟLFiFEjLWRiQFөWKӇWӭFOjFiFTX\WҳFWuPNLӃP
FKӍiSGөQJULrQJFKRPӝWEjLWRiQQjRÿyYjNKLiSGөQJFKRFiFEjL
WRiQNKiFWKuFҫQFyQKӳQJTX\WҳFNKiFSKKӧSFKREjLWRiQÿy&iF
TX\WҳFQj\WK{QJWKѭӡQJÿѭӧF[k\GӵQJGӵDWUrQNLӃQWKӭFFKX\rQ
JLDYjNLQKQJKLӋP'RYұ\FiFSKѭѫQJSKiSWuPNLӃPWKHRTX\WҳF
ORҥLQj\WKѭӡQJEӏEӓUѫLYjRFӵFWUӏFөFEӝFӫDEjLWRiQYjKҥQFKӃ
WURQJӭQJGөQJGRSKҧL[k\GӵQJOҥLEӝTX\WҳFFKRWӯQJEjLWRiQNKiF
nhau.
- &iF SK˱˯QJ SKiS WuP NL͇P FDR F̭S PHWD-heuristic): &iF SKѭѫQJ
SKiSWuPNLӃP ORҥL Qj\WKѭӡQJÿӝFOұS YӟLEjLWRiQWӭFOjYLӋFWuP
NLӃPGӵDWUrQTX\WҳFULrQJFӫDSKѭѫQJSKiSKѫQOjSKөWKXӝFYjREjL
8
WRiQ+LӋQQD\FiFSKѭѫQJSKiSQj\ÿѭӧFVӱGөQJUӝQJUmLQKҩWWURQJ
FiFEjLWRiQWӕLѭXQKҩWOjFiFEjLWRiQWӕLѭXWURQJKӋWKӕQJÿLӋQ7X\
QKLrQYLӋFVӱGөQJFiFSKѭѫQJSKiSQj\FNJQJFzQKҥQFKӃOjSKҧL[iF
ÿӏQK FiF WK{QJ Vӕ ÿLӅX NKLӇQ FӫD SKѭѫQJ SKiS QKѭ Vӕ Fi WKӇ WURQJ
TXҫQWKӇVӕWKӃKӋKD\FiFWK{QJVӕNKiFFKRWӯQJEjLWRiQNKiFQKDX
FiFWK{QJVӕQj\ҧQKKѭӣQJÿӃQFKҩWOѭӧQJFӫDOӡLJLҧL
- &iF SK˱˯QJ SKiS WuP NL͇P W WKtFK QJKL K\per ± heuristic): /RҥL
SKѭѫQJSKiSQj\ÿѭӧFSKiWWULӇQӣPӝWPӭFÿӝFDRKѫQFiFSKѭѫQJ
SKiSWuPNLӃPFDRFҩSĈLӇPÿһFELӋWFӫDFiFSKѭѫQJSKiSORҥLQj\
Oj NK{QJ JLDQ WuP NLӃP FӫD FK~QJ NK{QJ SKҧL Oj NK{QJ JLDQ WK{QJ
WKѭӡQJPjOjNK{QJJLDQFӫDKHXULVWLFKRһFPHWD± KHXULVWLFV7KӵF
WӃ FiF SKѭѫQJ SKiS WuP NLӃP Wӵ WKtFK QJKL Fy WKӇ ÿѭӧF FRL QKѭ Oj
³KHXULVWLFV ÿӇ WuP NLӃP KHXULVWLFV´ NKiF YӟL ³KHXULVWLFV ÿӇ WҥR UD
KHXULVWLFV´+LӋQQD\FiFSKѭѫQJSKiSQj\PӟLFKӍÿѭӧFÿӏQKKѭӟQJ
SKiWWULӇQYjFKѭDÿѭӧFSKәELӃQ
1.3.3. 3K˱˯QJSKiSODL
&iFSKѭѫQJSKiSODLFNJQJWKѭӡQJÿѭӧFVӱGөQJWURQJYLӋFJLҧLFiFEjLWRiQ
WӕLѭX&iFSKѭѫQJSKiSODLWKѭӡQJÿѭӧF[k\GӵQJGӵDWUrQNӃWKӧSJLӳDFiF
SKѭѫQJSKiSFәÿLӇQYjFiFSKѭѫQJSKiSWuPNLӃPKRһFJLӳDFiFSKѭѫQJ
SKiS WuP NLӃP YӟL QKDX 0өF ÿtFK FӫD FiF SKѭѫQJ SKiS ODL Oj WҥR UD FiF
SKѭѫQJSKiSPӟLÿӇNӃWKӯDFiFѭXÿLӇPFӫDFiFSKѭѫQJSKiSWKjQKSKҫQ
FNJ'RÿyFiFSKѭѫQJSKiSODLWKѭӡQJWuPÿѭӧFFKҩWOѭӧQJOӡLJLҧLNKiWӕW
FKRFiFEjLWRiQSKӭFWҥS7X\QKLrQFiFSKѭѫQJSKiS ODLNK{QJÿҧPEҧR
KRjQWRjQYӅFKҩWOѭӧQJOӡLJLҧLWӕWYuWtQKQJүXQKLrQFӫDFiFSKѭѫQJSKiS
WuPNLӃP+ѫQQӳDQKѭӧFÿLӇPFӫDFiFSKѭѫQJSKiSODLOjYLӋFiSGөQJUҩW
SKӭFWҥSYuFyQKLӅXWKDPVӕFҫQNLӇPVRiWQKLӅXEѭӟFFҫQWKӵFKLӋQYjWKӡL
gian tính tRiQNKiOkXGRVӵNӃWKӧSJLӳDFiFSKѭѫQJSKiS9uYұ\YLӋFiS
GөQJFiFSKѭѫQJSKiSODLFKRFiFEjLWRiQWӕLѭXÿzLKӓLQJѭӡLQJKLrQFӭX
FyQKLӅXNLQKQJKLӋPÿӇNLӇPVRiWWӕWTXiWUuQKWtQKWRiQ
9
&+ѬѪ1*7Ӕ,Ѭ8+Ï$7521*+ӊ7+Ӕ1*Ĉ,ӊ1
2.1. .KiLQLӋP
7ӕLѭXKyDWURQJKӋWKӕQJÿLӋQOjPӝWWұSKӧSFiFTX\ӃWÿӏQKYӅYLӋF[k\
GӵQJYұQKjQKEҧRWUu«FKRYLӋFVҧQ[XҩWWUX\ӅQWҧLYjSKkQSKӕLÿLӋQVDR
FKRKjPPөFWLrXOjWәQJFKLSKtFXQJFҩSÿLӋQÿӃQWҩWFҧFiFNKiFKKjQJOj
QKӓQKҩWQKѭQJYүQÿiSӭQJÿҫ\ÿӫFiFUjQJEXӝFYӅNӻWKXұWWKӏWUѭӡQJYj
ÿLӅXÿӝ7KӵFWӃYҩQÿӅWӕLѭXKyDWURQJKӋWKӕQJÿLӋQFNJQJQKҵPFҧLWKLӋQ
FiF\ӃXWӕWURQJYұQKjQKKѫQOjFKLSKtQKѭOjÿӝWLQFұ\KLӋXTXҧNLQKWӃ
P{LWUѭӡQJYjDQQLQK
- Ĉ͡WLQF̵\ JLҧPWKLӇXFKLSKtQJҳWÿLӋQQKLӉXFKҩWOѭӧQJÿLӋQQăQJ
JLҧPWKLӇX[iFVXҩWYjKұXTXҧFӫDYLӋFVөSÿәKӋWKӕQJEӏODQWUX\ӅQ
- .LQKW͇ WLӃSWөFKҥJLiÿLӋQJLҧPOѭӧQJFKLSKtFKRNKiFKKjQJYj
WҥRWKrPYLӋFOjP
- +L͏XTX̫ JLҧPFKLSKtVҧQ[XҩWSKkQSKӕLYjWLrXWKөÿLӋQ
- Môi WU˱ͥQJ JLҧPNKtWKҧLEҵQJFiFKFKRSKpSVӵWKDPJLDFӫDQăQJ
OѭӧQJWiLWҥRYjFҧLWKLӋQKLӋXVXҩWFiFNKkXVҧQ[XҩWWUX\ӅQWҧLSKkQ
SKӕLYjWLrXWKөÿLӋQQăQJ
- An ninh: JLҧPVӵSKөWKXӝFYjRQKұSNKҭXQăQJOѭӧQJFNJQJQKѭOjP
JLҧP[iFVXҩWYjKұXTXҧGRWiFÿӝQJFӫDWKLrQQKLrQYjFRQQJѭӡL
&iFEjLWRiQWӕLѭXWURQJKӋWKӕQJÿLӋQWKѭӡQJÿӅFұSÿӃQFiFOƭQKYӵFVDX
ÿk\
- 4X\ KR̩FK TX\ KRҥFK KӋ WKӕQJ ÿLӋQ Oj PӝW TXi WUuQK QKҵP ÿL ÿӃQ
TX\ӃWÿӏQKKRһFOj[k\PӟLKRһFOjQkQJFҩSFiFSKҫQWӱFӫDKӋWKӕQJ
ÿLӋQ KLӋQKӳXQKѭQKjPi\ÿLӋQWUҥPELӃQiSFiFÿѭӡQJGk\WUX\ӅQ
WҧLKD\FiSFiFWөÿLӋQKD\FXӝQNKiQJÿӇÿiSӭQJQKXFҫXSKөWҧL
WURQJWѭѫQJODLÿѭӧFGӵEiRWUѭӟF
- 9̵QKjQKYjÿL͉XNKL͋Q YұQKjQKKӋWKӕQJÿLӋQOjWұSKӧSFiFWKDR
WiFQKҵPGX\WUuFKӃÿӝ OjP YLӋFEuQKWKѭӡQJFӫDKӋWKӕQJÿLӋQÿӇ
ÿҧPEҧRFKҩWOѭӧQJÿӝWLQFұ\YjWtQKNLQKWӃFӫDKRҥWÿӝQJFXQJFҩS
ÿLӋQ'RÿLӋQQăQJNK{QJWKӇGӵWUӳYӟLGXQJOѭӧQJOӟQQrQFҫQFy
QJXӗQSKiWGӵWUӳYjÿLӅXNKLӇQÿѭӧFÿӇÿiSӭQJ\rXFҫXWKDXÿәLOLrQ
10
WөF FӫD SKө WҧL 9u Yұ\ KӋ WKӕQJ ÿLӋQ OX{Q ÿѭӧF JLiP ViW Yj ÿLLӅX
NKLӇQEӣLFRQQJѭӡL
2.2. &iFSKѭѫQJSKiSWӕLѭXKyDWURQJKӋWKӕQJÿLӋQ
'RWtQKSKӭFWҥSNtFKWKѭӟFOӟQYjÿDGҥQJFӫDFiFEjLWRiQWӕLѭXWURQJ
KӋWKӕQJÿLӋQFiFSKѭѫQJSKiSWӕLѭXiSGөQJWURQJKӋ WKӕQJÿLӋQFҫQSKҧL
ÿӫKLӋXTXҧÿӇJLҧLTX\ӃWÿѭӧFFiFYҩQÿӅQj\&iFSKѭѫQJSKiSWӕLѭXiS
GөQJFKRFiFEjLWRiQWURQJKӋWKӕQJÿLӋQEDRJӗPPӝWVӕQKyPFKtQKQKѭ
sau:
- +͏FKX\rQJLD còn gӑi là hӋ thӕng dӵa tri thӭc, là mӝt FKѭѫQJWUuQK
máy tính chӭa mӝt sӕ tri thӭFÿһc thù cӫa mӝt hoһc nhiӅu chuyên gia
FRQQJѭӡi vӅ mӝt chӫ ÿӅ cө thӇ QjRÿy'ҥng phә biӃn nhҩt cӫa hӋ
chuyên gia là mӝWFKѭѫQJWUuQKJӗm mӝt tұp luұt phân tích thông tin
WKѭӡQJÿѭӧc cung cҩp bӣLQJѭӡi sӱ dөng hӋ thӕng) vӅ mӝt lӟp vҩn
ÿӅ cө thӇFNJQJQKѭÿѭDUDFic phân tích vӅ các vҩQÿӅ ÿyYjW\WKHR
thiӃt kӃ FKѭѫQJWUuQKPjÿѭDOӡi khuyên vӅ trình tӵ FiFKjQKÿӝng cҫn
thӵc hiӋQÿӇ giҧi quyӃt vҩQÿӅĈk\OjPӝt hӋ thӕng sӱ dөng các khҧ
QăQJ Oұp luұQ ÿӇ ÿҥt tӟi các kӃt luұn. HiӋQ QD\ ÿm Fy Uҩt nhiӅu hӋ
chuyên giDÿѭӧc phát triӇn cho viӋc vұQKjQKYjÿLӅu khiӇn hӋ thӕng
ÿLӋn.
- 0̩QJ QHXUDO QKkQ W̩R KD\ WKѭӡQJ JӑL QJҳQ JӑQ Oj PҥQJ
neural (Artificial Neural network - ANN hay Neural Network) là
PӝW P{KuQKWRiQKӑF hay mô hình tính toán ÿѭӧF[k\GӵQJGӵDWUrQ
các PҥQJ QHXUDO VLQK KӑF 1y JӗP Fy PӝW QKyP các neural nhân
WҥR Q~WQӕLYӟLQKDXYj[ӱOêWK{QJWLQEҵQJFiFKWUX\ӅQWKHRFiF
NӃWQӕLYjWtQKJLiWUӏPӟLWҥLFiFQ~WFiFKWLӃSFұQFRQQHFWLRQLVPÿӕL
YӟL tính toán 7URQJ QKLӅX WUѭӡQJ KӧS PҥQJ QHXUDO QKkQ WҥR Oj
PӝW KӋ WKӕQJ WKtFK ӭQJ (adaptive system Wӵ WKD\ ÿәL FҩX WU~F FӫD
PuQKGӵDWUrQFiFWK{QJWLQErQQJRjLKD\ErQWURQJFKҧ\TXDPҥQJ
WURQJTXiWUuQKKӑF7URQJWKӵFWӃPҥQJQHXUDOÿѭӧFӭQJ GөQJSKә
ELӃQWURQJKӋWKӕQJÿLӋQÿһFELӋWOjWURQJJLiPViWYjÿLӅXNKLӇQ
- /RJLFPͧ)X]]\ORJLF ÿѭӧc phát triӇn tӯ lý thuyӃt tұp mӡ ÿӇ thӵc
hiӋn lұp luұn mӝt cách xҩp xӍ thay vì lұp luұn chính xác theo lôgic vӏ
tӯ cә ÿLӇn. Lôgic mӡ có thӇ ÿѭӧc coi là mһt ӭng dөng cӫa lý thuyӃt
tұp mӡ ÿӇ xӱ lý các giá trӏ trong thӃ giӟi thӵc cho các bài toán phӭc
- Xem thêm -