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Doç. Dr. Oğuz ŞİMŞEK
Dr. Çağrı AKGÜN
Öğr. Gör. Çetin İZGİ
KAFKASYA
ARAŞTIRMALARI -II-
Kitabın Adı :KAFKASYAARAŞTIRMALARI-II
Editör :Doç.Dr.OğuzŞİMŞEK,Dr.ÇağrıAKGÜN,Öğr.Gör.ÇetinİZGİ
Yazar :OğuzŞİMŞEK,XanəliKərimli,ÇağrıAKGÜN,SalimSerkanNAS,
UğurPARLAK,VildanYAVUZAKINCI,ÇetinİZGİ,
DilşadHuriyeKAYIRANİZGİ,HakanDuman,YunusEmreKök
Kapak / Mizanpaj :YağmurARDUÇ
1. Baskı :Aralık2024ANKARA
Yayın Koordinatörü :CeydaŞEREFLİOĞLU
Yayın Yönetmeni :SelvaALİM
ISBN :978-625-5537-20-1
Yayın No. :2728
© Tüm hakları yazarına aittir. Yazarın izni alınmadan kitabın tümünün veya bir kısmının
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İÇİNDEKİLER
ÖNSÖZ ............................................................................................................... iii
BAYAN CHANTRE’NİN 1890 YILI GÜNEY KAFKASYA SEYHAT
NOTLARINDA IĞDIR VE ÇEVRESİ
Oğuz ŞİMŞEK ............................................................................................................................................1
NAXÇIVAN POEZİYASINDA VƏTƏNPƏRVƏRLİK MOTİVLƏRİ
Xanəli Kərimli ......................................................................................................................................57
KAFKASYA’DA SINIRAŞAN SULAR SORUNU:
ARAS HAVZASI VE TÜRKİYE’NİN BARAJ POLİTİKALARI
Çağrı AKGÜN - Salim Serkan NAS ........................................................................................75
THEMATIC MAPPING OF AGRICULTURAL AND RURAL RESEARCH IN
DAGESTAN
Duman, Hakan ................................................................................................................................. 99
KONAKLAMADA YENİ TREND AKILLI OTELLER: KAFKASYA VE
TÜRKİYE İNCELEMESİ
Uğur PARLAK .......................................................................................................................................127
BİBLİYOMETRİK YAKLAŞIMLA KAFKASYA EKONOMİSİ:
LİTERATÜRDEKİ EĞİLİMLER VE KAVRAMSAL ÇERÇEVE
Vildan YAVUZ AKINCI - Çetin İZGİ ....................................................................................... 141
ENERJİ JEOPOLİTİĞİ: TÜRKİYE VE KAFKASYA’NIN AVRUPA BİRLİĞİ
İÇİN ÖNEMİ
Dilşad Huriye KAYIRAN İZGİ ....................................................................................................... 161
MACHINE LEARNING-BASED CLASSIFICATION OF COUNTRIES
BASED ON FOOD SUPPLY QUANTITIES IN THE CAUCASUS AND
SURROUNDING REGIONS
Duman, Hakan ................................................................................................................................ 189
TÜRKİYE VE AZERBAYCAN’DA SOSYAL GÜVENLİK SİSTEMLERİNİN
KARŞILAŞTIRMASI
Yunus Emre Kök .............................................................................................................................209
Hakan Duman 189
MACHINE LEARNING-BASED CLASSIFICATION OF
COUNTRIES BASED ON FOOD SUPPLY QUANTITIES IN
THE CAUCASUS AND SURROUNDING REGIONS
Duman, Hakan*
INTRODUCTION
1 2
3
4
*
1 “Iğdır ılinde Kırsal Kalkınma Kooperatifi
Üyelerinin Örgütlenme Ve Kooperatif Faaliyetleriyle ılgili Problemleri Ve Çözüm Önerilerinin
BelirlenmesiThird Sector Social Economic Review
2
3 “Introduction to Agricultural
Economics,”, 6th ed. Pearson, Essex
4 FAO
190 KAFKASYA ARAŞTIRMALARI-II
5
6
7
89 1011
5 Food Programme; Earthscan
6 FAO
7 “Food security,” NASA; IPCC
8 “Machine Learning in Agriculture: A
Review,” Sensors
9 “Machine Learning Applications for Precision
Agriculture: A Comprehensive Review,” IEEE Access
10 “Machine Learning in Agriculture: A
Comprehensive Updated Review,” Sensors
11
Hakan Duman 191
12
13
14
15
16
17
18
19
20
21
12
13 “IMPACT OF MACHINE learning
ON Management, healthcare AND AGRICULTURE,” Materials Today: Proceedings
14
15 “Neural network-based clustering for agriculture
management,” EURASIP Journal on Advances in Signal Processing,
16
17
18
19
20
21
192 KAFKASYA ARAŞTIRMALARI-II
22
MATERIALS AND METHODS
23
22 “Kafkasya’nın Ekonomik Dinamikleri: Azerbaycan, Gürcistan Ve
Ermenistan’ın Türkiye ile Ticari Ve Stratejik Bağlantıları,” Kafkasya Araştırmaları -I
23 The Food; Agriculture Organization
(FAO)
Hakan Duman 193
24
25
26
27
24 “On the Comparison of Several Mean Values: An Alternative
Approach,” Biometrika
25 “Comparison of Post Hoc Tests for Unequal
Variance,” International Journal of New Technologies in Science and Engineering
26 “An R Companion to Applied Regression,” SAGE
27 “Applied predictive modeling,Springer
194 KAFKASYA ARAŞTIRMALARI-II
28 29 30
31
32 33
34
35 3637
38
39
28 “Logistic Regression,” Circulation
29 “Logistic Regression,” Topics in Biostatistics,
Ambrosius, W.T. Humana Press
30
31 “Applied Logistic Regression”, 2nd ed. Wiley
32
33
34 “Hands-on machine learning with R,” Chapman;
35 “Practical Machine Learning in R,”Wiley,
36 “Decision tree modeling using R,” Annals of Translational Medicine
37 “Karar Ağacı Optimizasyon Algoritması üzerine Bir
Çalışma,” Journal of the Institute of Science and Technology
38 “Induction of decision trees,” Machine Learning,
39 “Classification and regression
trees,” Chapman & Hall,
Hakan Duman 195
40
41
42 43
44
45
46
40
41 “Random forests,” Machine Learning,
42
43 “Hands-on machine learning with scikit-learn and tensorflow: Concepts,
tools, and techniques to build intelligent systems”
44 “A logical calculus of the ideas immanent in
nervous activity,” The Bulletin of Mathematical Biophysics
45 “Deep learning: methods and applications,” Foundations
and Trends in Signal Processing
46
196 KAFKASYA ARAŞTIRMALARI-II
47
48
49 50
51
52
53
54
47 “Data Envelopment Analysis
with R,” Springer
48 “Measuring the efficiency of decision
making units,” European Journal of Operational Research
49 “Some Models for Estimating
Technical and Scale Inefficiencies in Data Envelopment Analysis,” Management Science
50 “Productivity and Efficiency Measurement of Airlines: Data
Envelopment Analysis Usingr” Elsevier
51 “R: A Language and Environment for Statistical Computing,” R
Foundation for Statistical Computing
52 “Welcome to the tidyverse,” Journal of
Open Source Software,
53
54
Hakan Duman 197
55 56
57
58
RESULTS AND DISCUSSION
Figure 1. Map highlighting the countries included in the study
55
56
57 “Scikit-Learn: Machine Learning
in Python,” Journal of Machine Learning Research
58
198 KAFKASYA ARAŞTIRMALARI-II
Table 1. Mean supply of animal products (kcal/capita/day)
*
a
c
e
* Values with the same letter are not signicantly different at p < 0.05.
Hakan Duman 199
Table 2. Mean supply of vegetal products (kcal/capita/day)
*
a
c
* Values with the same letter are not signicantly different at p < 0.05.
200 KAFKASYA ARAŞTIRMALARI-II
Figure 2. Box plots illustrating the supply distribution of animal and vegetal products
(kcal/capita/day)
Hakan Duman 201
Figure 3. Plots illustrating the annual changes in the supply distribution of animal and
vegetal products (kcal/capita/day)
Fp
Fp
Table 3. Mean weighted F1 scores of machine learning models used in the study
*
a
a
*Values with the same letter are not signicantly different at p < 0.05.
202 KAFKASYA ARAŞTIRMALARI-II
F
p
F
p
Table 4. Mean time spent on ne-tuning machine learning models (in seconds)
*
a
c
*Values with the same letter are not signicantly different at p < 0.05.
Hakan Duman 203
Table 5. CRS-DEA efciency scores of machine learning models, using time as input
and performance as output
Table 6. Highest-performing sub-models of studied algorithms, along with their trai-
ning and test scores and ne-tuned hyperparameters.
-
-
-
204 KAFKASYA ARAŞTIRMALARI-II
CONCLUSION
Hakan Duman 205
ACKNOWLEDGEMENTS
Statement:
206 KAFKASYA ARAŞTIRMALARI-II
REFERENCES
“Karar Ağacı Optimizasyon Algoritması üzerine Bir Çalışma”,
“Some models for estimating technical
and scale ineiciencies in data envelopment analysis”
“Machine learning in agriculture: A
comprehensive updated review”,
“Random forests”,
“Measuring the eiciency of decision
making units”,
“Deep learning: methods and applications”,
“Iğdır ı
linde kırsal kalkınma kooperatifi
üyelerinin örgütlenme ve kooperatif faaliyetleriyle ı
lgili problemleri ve çözüm
önerilerinin belirlenmesi”
Hakan Duman 207
“Logistic Regression”,
“Machine learning in agriculture: A
review”,
“A logical calculus of the ideas immanent in nervous
activity”
“IMPACT OF MACHINE learning
ON Management, healthcare AND AGRICULTURE”
“Scikit-learn: Machine learning in
Python”,
“Induction of decision trees”
“Current and future applications
of statistical machine learning algorithms for agricultural machine vision systems”,
“Machine learning applications for precision
agriculture: A comprehensive review”
“Comparison of post hoc tests for unequal variance”
208 KAFKASYA ARAŞTIRMALARI-II
“Neural network-based clustering for agriculture
management”,
“On the comparison of several mean values: An alternative approach”
“Welcome to the tidyverse”,
“Decision tree modeling using R”,
