JURNAL ILMIAH Judul Karya Ilmiah (Artikel) : Stock Pri

HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW KARYA ILMIAH : JURNAL ILMIAH

Judul Karya Ilmiah (Artikel) : Stock Price Modeling Using Localized Multiple Kernel Learning Support Vector Machine

Jumlah Penulis : 4 Orang Penulis ke : 1

Nama Penulis : Hasbi Yasin, Rezzy Eko Caraka, Abdul Hoyyi, Sugito Identitas Jurnal Ilmiah

a. Nama Jurnal : ICIC Express Letters Part B: Applications

b. Nomor ISSN : 0973-1768

c. Volume, No, Bulan, Tahun : Vol. 11 No. 4, April 2020, pp. 333-339

d. Penerbit : IEEE

e. DOI artikel (jika ada) : DOI: 10.24507/icicelb.11.04.333

f. Alamat web jurnal : http://www.icicelb.org/ellb/contents/2020/4/elb-11-04-03.pdf g. Indexing : Scopus (Elsevier), INSPEC (IET)

Kategori Publikasi Jurnal Ilmiah : Jurnal Ilmiah Internasional / Internasional Bereputasi (beri pada kategori yang tepat) Jurnal Ilmiah Nasional Terakreditasi

Jurnal Ilmiah Nasional/Nasional Terindeks di DOAJ, CABI Hasil Penilaian Peer Review :

Komponen Yang Dinilai

Nilai Reviewer

Nilai Rata-rata Reviewer I Reviewer II

a. Kelengkapan unsur isi buku (10%) 3 3 3

b. Ruang lingkup dan kedalaman pembahasan (30%)

10,5 10 10,25

c. Kecukupan dan kemutahiran data/informasi dan metodologi (30%)

10,5 11 10,75

d. Kelengkapan unsur dan kualitas penerbit (30%)

10 10 10

Total = (100%) 34 34 34

Semarang, 16 Juni 2020 Reviewer 2

Dr. Rukun Santoso, M.Si.

NIP. 19650225 199201 1 001 Unit kerja :

Departemen Statistika Undip

Reviewer 1

Prof. Drs. Mustafid, M.Eng., Ph.D.

NIP. 19550528 198003 1 002 Unit kerja :

Departemen Statistika Undip



KARYA ILMIAH ^: JURIIAL ILMIAH

Judul Karya Ilmiah (Artikel) Jumlah Penulis

Nama Penulis

Identitas Jurnal Ilmiah

a.

Nama Jurnal

b.

Nomor ISSN

c. Volume, No, Bulan, Tahun d. Penerbit

e.

DOI artikel (ika

ada)

f. Alamat

web

jurnal g. Indexing

Kategori Publikasi Jurnal Ilmiah

^:

(beri /pada kategori yang tepat)

Stock Price Modeling Using Localized Multiple Kemel Learning Support Vector Machine

4 ^{Orang Penulis ke :} i

Hasbi Yasin, Rezzy Eko Caraka, Abdul Hoyyi, Sugito ICIC Express Letters

Part

B: Applications

0973-1768

Vol.

¹ 1

No. 4, Aptil 2020, pp. 333-339 IEEE

DOI:

^I

0.24507licicelb.

I

1.04.333

http://wwu,. icicelb.org/el lb/contents/2020/4lelb-

1 i

-04-03.pdf

Scopus

(Elsevier), INSPEC (fET)

l-4 ^{Jurnal Ilmiah} +ntemasie+al / Internasional Bereputasi Jurnal Ilmiah Nasional Terakreditasi

I ^lr*uf IkniahNasionalA.Iasional Terindeks di DOAI CABI

Hasil Penilaian Peer Review

:

Komponen Yang Dinilai

Nilai Maksimal Jurnal IImiah :40 _Nilai Akhir

Yang Diperoleh Internasional

Bereputasi Internasional

^Nasional

Terakreditasi

Nasional Tidak Terakreditasi

Nasional

Terindeks DOAJdII.

a.

Kelengkapan unsur isi buku

(10%) ^{4 3,0}

b.

^Ruang

^lingkup

dan kedalaman

pembahasan (30%)

t2

10,0

c.

^{Kecukupan dan} kemutahiran datalinformasi dan metodologi

B0%\

12 10,5

d.

Kelengkapan unsur dan kualitas

oenerbit ^{(30%o) 12}

10,5

Totat : (100%)

40

34,0

Kontribusi

Pengusul (Penulis

Pertama) = 60ohx34,0:20,4

Komentar

Peer

Review:

a. Kelengkapan

dan kesesuaiao

unsur: Cukup baik. Sistematika

b.

c.

penulisan artikel menggunakan

sistematika

jurnal statistika terapan, namun meliputi: introduction, methods, discussion

dan

conclusions.

Artikel ditulis

dengan Bahasa

Inggns cukup baik.

Setiap bab

berisi isi yang

sesuai dengan

masing-masing tujuan.

Ruang lingkup

dan

kedalaman pembahasan: Cukup baik dengan materi artikel berhubungan

dengan

penerapan statistika. Kedalaman

pembahasan secara

scientific lebih fokus

pembahasan pada aspek

komputasi.

Kecukupan

dan

kemutahiran datalinformasi

dan

metodologi: Cukup baik, namun isi materi

dan

hasil penelitian belum focus pda

kemutakhiran dalam teori

atau

metodologi. Isi artikel menggunakan metode yang

sudah ada.

Artikel menggunakan 28 referensi dan

sebagian

besar

10

tahun terakhir

Kelengkapan unsur

dan

kualitas penerbit: Artikel dipublikasikan

pada

"ICIC Express Letters Part B: Applications" tahun 2020, terindeks di ^{SCOPUS, nilai}

^SJR

2018= 0,147, quartile ranking _Q4,

dengan

terbitan

setiap

bulanan

Indikasi Plagiasi: Tidak

^ada.

Prof. Drs. Mustafid, M.Eng., Ph.D.

NIP. 19550528 198003 l

⁰⁰²

Unit kerja:

Departemen Statistika Undip

Jabatan

Fungsional:

Guru Besar

d.

e.

Semarang,

HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW KARYA ILMIAH : JURNAL ILMIAH

Judul Karya Ilmiah (Artikel) : Stock Price Modeling Using Localized Multiple Kernel Learning Support Vector Machine

Jumlah Penulis : 4 Orang Penulis ke : 1

Nama Penulis : Hasbi Yasin, Rezzy Eko Caraka, Abdul Hoyyi, Sugito Identitas Jurnal Ilmiah

a. Nama Jurnal : ICIC Express Letters Part B: Applications

b. Nomor ISSN : 0973-1768

c. Volume, No, Bulan, Tahun : Vol. 11 No. 4, April 2020, pp. 333-339

d. Penerbit : IEEE

e. DOI artikel (jika ada) : DOI: 10.24507/icicelb.11.04.333

f. Alamat web jurnal : http://www.icicelb.org/ellb/contents/2020/4/elb-11-04-03.pdf g. Indexing : Scopus (Elsevier), INSPEC (IET)

Kategori Publikasi Jurnal Ilmiah : Jurnal Ilmiah Internasional / Internasional Bereputasi (beri pada kategori yang tepat) Jurnal Ilmiah Nasional Terakreditasi

Jurnal Ilmiah Nasional/Nasional Terindeks di DOAJ, CABI

Hasil Penilaian Peer Review :

Komponen Yang Dinilai

Nilai Maksimal Jurnal Ilmiah = 40 Nilai Akhir

Yang Diperoleh Internasional

Bereputasi Internasional Nasional Terakreditasi

Nasional Tidak Terakreditasi

Nasional Terindeks DOAJ dll.

a. Kelengkapan unsur isi buku

(10%) 4 3

b. Ruang lingkup dan kedalaman

pembahasan (30%) 12 10

c. Kecukupan dan kemutahiran data/informasi dan metodologi

(30%) 12 11

d. Kelengkapan unsur dan kualitas

penerbit (30%) 12 10

Total = (100%) 40 34

Kontribusi Pengusul (Penulis

Utama) (60%x34) = 20,4

Komentar Peer Review:

a. Kelengkapan dan kesesuaian unsur:

Unsur isi lengkap, Bahasa Inggris cukup baik b. Ruang lingkup dan kedalaman pembahasan:

Penekanan pada komputasi, pembahasan cukup baik, bahasan pengaruh parameter terhadap keadaan optimal kurang mendalam c. Kecukupan dan kemutahiran data/informasi dan metodologi:

Informasi disampaikan dengancara yang baik d. Kelengkapan unsur dan kualitas penerbit:

Terindeks Scopus Q4 e. Indikasi Plagiasi:

Tidak ada

f. Kesesuaian bidang ilmu:

Sesuai bidang Statistika dan komputasi.

Semarang, Reviewer 2

Dr. Rukun Santoso, M.Si.

NIP. 19650225 199201 1 001

Unit kerja:

Departemen Statistika Undip Jabatan Fungsional:

Lektor Kepala



Document details

1 of 28

Stock price modeling using localized multiple kernel learning support vector machine

(Article)

, , ,

Department of Statistics, Diponegoro University, Tembalang, Central Java 50275, Indonesia

College of Informatics, Chaoyang University of Technology, No. 168, Jifeng East Road, Wufeng District, Taichung, 41349, Taiwan

Abstract

Effectively and efficiently learning an optimal kernel is of great importance to the success of kernel method. Along with this line of research, many pioneering kernel learning algorithms have been proposed, developed and combined in many ways. This paper aims to explain the application of Localized Multiple Kernel Learning Support Vector Machine (LMKL-SVM) to predict the daily stock price of PT.XL Axiata Tbk (EXCL), PT.Indofood SuksesMakmur Tbk (INDF) and PT.Unilever Indonesia Tbk (UNVR) from January 2014 to May 2016. It can be concluded that LMKL-SVM has good performance to predict daily stock price with Mean Absolute Percentage Error (MAPE) produced all less than 2%. © 2020 ICIC International.

Author keywords

Localized SVM Multi kernel Stock price Time series

Funding details

Funding sponsor Funding number Acronym

Universitas Diponegoro 329-44/UN7.P4.3/PP/2019 UNDIP

Lembaga Penelitian dan Pengabdian Kepada Masyarakat LPPM

Lembaga Penelitian dan Pengabdian Kepada Masyarakat LPPM

Funding text

Acknowledgment. This research fully supported by Institute for Research and Community Services (LPPM) Diponegoro University, under contract 329-44/UN7.P4.3/PP/2019.

◅ Back to results Next ▻

#

Export

$

Download

%

Print

&

E-mail

'

Save to PDF

⋆

Save to list More...

▻

View at Publisher

ICIC Express Letters, Part B: Applications Volume 11, Issue 4, April 2020, Pages 333-339

Yasin, H.^a & Caraka, R.E.^b& Hoyyi, A.^a Sugito^a ) Save all to author list

a b

*

View references (28)

PlumX Metrics

Usage, Captures, Mentions, Social Media and Citations beyond Scopus.

Metrics

Cited by 0 documents

Inform me when this document is cited in Scopus:

Related documents

, ,

(2019) Sylwan

, ,

(2019) AIP Conference Proceedings

, ,

(2019) International Journal of Advances in Soft Computing and its Applications

❓ View all metrics ▻

*

Set citation alert ▻ ▻ Set citation feed

Some new construction of seasonal smooth support vector regression firefly algorithm in electrical load forecasting Toharudin, T. Caraka, R.E.

Chen, R.-C.

Rainfall forecasting multi kernel support vector regression seasonal autoregressive integrated moving average (MKSVR-SARIMA) Caraka, R.E. Bakar, S.A.

Tahmid, M.

Copula-based feedforward neural network genetic algorithm cargo forecasting

Toharudin, T. Caraka, R.E.

Bachrudin, A.

RC RC

Search Sources Lists SciVal ↗

References (28)

Segel, E., Heer, J.

(2010) IEEE Transactions on Visualization and Computer Graphics, 16 (6), art. no. 5613452, pp. 1139-

1148. .

doi: 10.1109/TVCG.2010.179

Sra, S., Nowozin, S., Wright, S.J.

(2019) Optimization for Machine Learning. . MIT Press

Fu, T.-C.

(2011) Engineering Applications of Artificial Intelligence, 24 (1), pp. 164-181. . doi: 10.1016/j.engappai.2010.09.007

Caraka, R.E., Chen, R.C., Toharudin, T., Pardamean, B., Bakar, S.A., Yasin, H.

(2019) IAENG International Journal of Computer Science, 46 (4). .

Rüping, S.

(2001) SVM Kernels for Time Series Analysis, p. 8. . Univ. Dortmund

Wang, X.

(2018) International Journal of Innovative Computing, Information and Control, 14 (1), pp. 261-277.

.

doi: 10.24507/ijicic.14.01.261

Wang, X.

ISSN: ISSN: 21852766 Source Type: Source Type: Journal Original language: Original language: English

DOI:

DOI: 10.24507/icicelb.11.04.333 Document Type:

Document Type: Article Publisher:

Publisher: ICIC International

▻ View in search results format All Export

%

Print

&

E-mail

'

Save to PDF Create bibliography

1

Narrative visualization: Telling stories with data

Cited 361 times

View at Publisher

2

Cited 251 times

3

A review on time series data mining

Cited 759 times

View at Publisher

4

Ramadhan short-term electric load: A hybrid model of cycle spinning wavelet and group method data handling (CSW-GMDH)

Cited 2 times http://www.iaeng.org/IJCS/current_issue.html

5

Cited 20 times

6

The plasticity and elasticity of stock price variations – part 1: Theory and techniques

Cited 2 times

http://www.ijicic.org/ijicic-140118.pdf

View at Publisher

7

The plasticity and elasticity of stock price variations - Part 2: Model analysis and application

Find more related documents in Scopus based on:

View all related documents based on references

▻

Authors Keywords ▻

(2018) International Journal of Innovative Computing, Information and Control, 14 (2), pp. 629-645.

Ding, S., Zhao, H., Zhang, Y., Xu, X., Nie, R.

(2015) Artificial Intelligence Review, 44 (1), pp. 103-115. . doi: 10.1007/s10462-013-9405-z

Tarno, Yasin, H., Warsito, B.

(2016) Global Journal of Pure and Applied Mathematics, 12 (2), pp. 1201-1210. .

Warsito, B., Santoso, R., Suparti, Yasin, H.

(Open Access) (2018) Journal of Physics: Conference Series, 1025 (1), art. no. 012097. . doi: 10.1088/1742-6596/1025/1/012097

Caraka, R.E., Chen, R.C., Toharudin, T., Pardamean, B., Yasin, H., Wu, S.H.

(Open Access)

(2019) IEEE Access, 7, art. no. 2950439, pp. 161654-161665. . doi: 10.1109/ACCESS.2019.2950439

Chang, C.-C., Lin, C.-J.

(2011) ACM Transactions on Intelligent Systems and Technology, 2 (3), art. no. 27. . doi: 10.1145/1961189.1961199

Yasin, H., Caraka, R.E., Tarnohoyyi, A.

Prediction of crude oil prices using support vector regression (SVR) with grid search – Cross validation algorithm

(2016) Glob. J. Pure Appl. Math., Vol, 4, p. 12.

Han, Y., Yang, K., Yang, Y., Ma, Y.

http://www.ijicic.org/contents.htm

8

Extreme learning machine: algorithm, theory and applications

Cited 156 times

View at Publisher

9

Constructing volatility model of portfolio return by using GARCH

Cited 2 times http://www.ripublication.com/gjpam16/gjpamv12n2_03.pdf

10

Cascade Forward Neural Network for Time Series Prediction

Cited 5 times http://iopscience.iop.org/journal/1742-6596

View at Publisher

11

Prediction of status particulate matter 2.5 using state Markov chain stochastic process and hybrid VAR-NN-PSO

Cited 2 times http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

View at Publisher

12

LIBSVM: A Library for support vector machines

Cited 19425 times

View at Publisher

13

14

Localized Multiple Kernel Learning With Dynamical Clustering and Matrix

Regularization

(2018) IEEE Transactions on Neural Networks and Learning Systems, 29 (2), art. no. 7792117, pp. 486-

499. .

doi: 10.1109/TNNLS.2016.2635151

Rakotomamonjy, A., Bach, F.R., Canu, S., Grandvalet, Y.

(2008) Journal of Machine Learning Research, 9, pp. 2491-2521. .

Caraka, R.E., Bakar, S.A.

(2018) Journal of Engineering and Applied Sciences, 13 (17), pp. 7440-7449. .

Platt, J.C.

(1998) Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines.

.

Nocedal, J., Wright, S.J.

Quadratic programming, in Numer (2006) Optim

Andersen, E.D.

(2009) Markowitz Portfolio Optimization Using MOSEK. .

Prastyo, D.D., Nabila, F.S., Suhartono, Lee, M.H., Suhermi, N., Fam, S.-F.

(2019) Communications in Computer and Information Science, 937, pp. 46-57. . ISBN: 978-981133440-5

doi: 10.1007/978-981-13-3441-2_4

Suhartono, Maghfiroh, B., Rahayu, S.P.

(2019) International Journal of Innovative Technology and Exploring Engineering, 8 (4S), pp. 212-218.

. Cited 7 times

http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5962385

View at Publisher

15

SimpleMKL

Cited 1077 times http://www.jmlr.org/papers/volume9/rakotomamonjy08a/rakotomamonjy08a.pdf

View at Publisher

16

Evaluation performance of Hybrid Localized Multi Kernel SVR (LMKSVR) in electrical load data using 4 different optimizations

Cited 11 times http://www.medwelljournals.com/archive.php?jid=1816-949x

17

Cited 4558 times

18

19

Cited 2 times

20

VAR and GSTAR-based feature selection in support vector regression for multivariate spatio-temporal forecasting

Cited 5 times http://www.springer.com/series/7899

View at Publisher

21

Hybrid VARX-SVR and GSTARX-SVR for forecasting spatio-temporal data

Cited 2 times

https://www.ijitee.org/archive/

Caraka, R.E., Bakar, S.A., Tahmid, M.

(2019) AIP Conference Proceedings, 2111, art. no. 020014. . ISBN: 978-073541843-1

doi: 10.1063/1.5111221

Karatzoglou, A., Hornik, K., Smola, A., Zeileis, A.

(2004) Journal of Statistical Software, 11, pp. 1-20. .

Cortes, C., Vapnik, V.

(Open Access)

(1995) Machine Learning, 20 (3), pp. 273-297. . doi: 10.1023/A:1022627411411

Gönen, M., Alpaydin, E.

(2011) Journal of Machine Learning Research, 12, pp. 2211-2268. .

Caraka, R.E., Bakar, S.A., Pardamean, B., Budiarto, A.

(2018) Proceedings - 2017 International Conference on Innovative and Creative Information Technology:

Computational Intelligence and IoT, ICITech 2017, 2018-January, pp. 1-6. . ISBN: 978-153864045-6

doi: 10.1109/INNOCIT.2017.8319127

Caraka, R.E., Bakar, S.A., Tahmid, M., Yasin, H., Kurniawan, I.D.

(Open Access)

(2019) Telkomnika (Telecommunication Computing Electronics and Control), 17 (4), pp. 1818-1827.

.

doi: 10.12928/TELKOMNIKA.v17i4.11788

Dinuzzo, F., Neve, M., De Nicolao, G., Gianazza, U.P.

22

Rainfall forecasting multi kernel support vector regression seasonal autoregressive integrated moving average (MKSVR-SARIMA)

Cited 4 times http://scitation.aip.org/content/aip/proceeding/aipcp

View at Publisher

23

kernlab - An S4 package for kernel methods in R

Cited 740 times http://www.jstatsoft.org/v11/i09/v11i09.pdf

View at Publisher

24

Support-Vector Networks

Cited 24138 times

View at Publisher

25

Multiple kernel learning algorithms

Cited 1061 times http://jmlr.csail.mit.edu/papers/volume12/gonen11a/gonen11a.pdf

View at Publisher

26

Hybrid support vector regression in electric load during national holiday season

Cited 6 times

View at Publisher

27

Neurocomputing fundamental climate analysis

Cited 9 times

http://journal.uad.ac.id/index.php?journal=TELKOMNIKA&page=issue&op=archive

View at Publisher

28

On the representer theorem and equivalent degrees of freedom of SVR

1 of 28

(2007) Journal of Machine Learning Research, 8, pp. 2467-2495. .

© Copyright 2020 Elsevier B.V., All rights reserved.

Cited 21 times http://jmlr.csail.mit.edu/papers/volume8/dinuzzo07a/dinuzzo07a.pdf

View at Publisher

◅ Back to results Next ▻ , Top of page

About Scopus

What is Scopus Content coverage Scopus blog Scopus API Privacy matters

Language

日本語に切り替える

Русский язык

Customer Service

Help Contact us

Copyright © . All rights reserved. Scopus® is a registered trademark of Elsevier B.V.

We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the .

Terms and conditions ↗ Privacy policy ↗ Elsevier B.V ↗

use of cookies

Source details ^{Feedback ▻} Compare sources ^▻

ICIC Express Letters, Part B: Applications

Scopus coverage years: from 2010 to Present Publisher: IEEE

ISSN: 2185-2766

Subject area: Computer Science: General Computer Science

View all documents ▻ Set document alert " Save to source list

CiteScore 2018

0.12 ^#

SJR 2018

0.147 ^#

SNIP 2018

0.174 ^#

CiteScore CiteScore rank & trend CiteScore presets Scopus content coverage

Calculated using data from 30 April, 2019

CiteScore

*CiteScore includes all available document types

0.12 ⁼ Citation Count 2018 Documents 2015 -

2017*

=

Metrics displaying this icon are compiled according to , a collaboration between industry and academia.

2018 ^{$ $}

127 Citations ▻ 1,020 Documents ▻

▻

View CiteScore methodology CiteScore FAQ ▻

Last updated on 09 April, 2020

CiteScoreTracker 2019

0.12 ⁼ Citation Count 2019 Documents 2016 - 2018

=

# Updated monthly

89 Citations to date ▻ 724 Documents to date ▻

↗

Snowball Metrics

CiteScore rank

Category Rank Percentile

Computer Science

#204/206 1st

#

General Computer Science

▻

View CiteScore trends Add CiteScore to your site 🔗

About Scopus

What is Scopus Content coverage Scopus blog Scopus API Privacy matters

Language

日本語に切り替える 切换到简体中⽂

切換到繁體中⽂

Русский язык

Customer Service

Help Contact us

Copyright © . All rights reserved. Scopus® is a registered trademark of Elsevier B.V.

↗

Terms and conditions Privacy policy ↗

Elsevier B.V ↗

Indexed by

Scopus (Elsevier), INSPEC (IET)

ICIC Express Letters, Part B: Applications

An International Journal of Research and Surveys

Thanks for visiting the Web site of ICIC Express Letters, Part B: Applications -- a peer-reviewed English language journal of research and surveys on Innovative Computing, Information and Control (abbreviated as ICIC). ICIC Express Letters, Part B: Applications is published by ICIC International monthly.

The primary aim of the ICIC Express Letters, Part B: Applications is to publish quality short papers (no more than 8 pages) of new developments and trends, novel techniques and approaches, innovative methodologies and technologies on the theory and applications of intelligent systems, information and control.

All submissions to this journal are processed through online submission system only. Each paper published in ICIC Express Letters, Part B: Applications will be assigned a DOI (Digital Object Identifier) number.

Steve P. Banks, UK Lakhmi C. Jain, Australia Peng Shi, Australia

Peter Fleming, UK Masaharu Mizumoto, Japan Junzo Watada, Malaysia

Tom Heskes, Netherlands Witold Pedrycz, Canada Takeshi Yamakawa, Japan

Jamal Ameen, UK Ozer Ciftcioglu, Netherlands Chao-Hsing Hsu, Taiwan, China Dongsoo Kim, Korea

Yao Liu, China

Tshilidzi Marwala, South Africa Ngoc Thanh Nguyen, Poland Arnulfo Luevanos Rojas, Mexico Masanori Takahashi, Japan Edwin Engin Yaz, USA

Michael V. Basin, Mexico Vasile Dragan, Romania Hamid Reza Karimi, Italy Huey-Ming Lee, Taiwan, China Magdi Mahmoud, Saudi Arabia Subhas Misra, India

Nikos Nikolaidis, Greece Takao Sato, Japan Bay Vo, Vietnam

Umi Kalsom Yusof, Malaysia

Yasar Becerikli, Turkey Kuniaki Fujimoto, Japan Sawai Pongswatd, Thailand Feng-Tse Lin, Taiwan, China Anatolii Martynyuk, Ukraine Sing Kiong Nguang, New Zealand Pavel Pakshin, Russia

Xiaojie Su, Chinan Yuanqing Wu, China Argyrios C. Zolotas, UK Editorial Board

Editors-in-Chief

Yan Shi, Tokai University, Japan

Ramesh Agarwal, Washington University, USA Advisory Board

Associate Editors

Aims and Scope of ICIC Express Letters, Part B: Applications

The ICIC Express Letters, Part B: Applications is a peer reviewed English language journal of research and surveys on Innovative Computing, Information and Control (abbreviated as ICIC), and is published by ICIC International monthly. The primary aim of the ICIC Express Letters, Part B: Applications is to publish quality short papers (no more than 8 pages) of new developments and trends, novel techniques and approaches, innovative methodologies and technologies on the theory and applications of intelligent systems, information and control.

The scope of the ICIC Express Letters, Part B: Applications is in the broad areas of intelligent systems, information and control, includes but not limited to:

Intelligent Systems and Innovative Computing

Artificial intelligence and expert systems, approximate reasoning, fuzzy systems and rough sets, fuzzy optimization and decision making, evolutionary computation, intelligent information systems, image and speech signal processing, human-machine learning, neural networks, knowledge discovery, data mining, clustering and data analysis, decision support systems, intelligent fault detection and identification, knowledge-based systems, hybrid intelligent systems, soft computing, management science.

Information and Control

Information theory and applications, optimal, adaptive, predictive, robust, fuzzy and reliable control and filtering on linear and nonlinear systems, stochastic systems, hybrid systems, supervisory systems, guidance and navigation systems, real-time systems, discrete event systems, signal and image processing, system identification, optimization techniques, robustness analysis, learning systems, fault detection, robotics and motion control, manufacturing systems, power systems, networked control systems, environmental and bio-engineering, complex and large scale systems, bioinformatics, control education, transportation systems

Scimago Journal & Country Rank

Home Journal Rankings Country Rankings Viz Tools Help About Us

ICIC Express Letters, Part B: Applications

Country United States  -  SIR Ranking of United States

12

H Index

Subject Area and

Category Computer Science

Computer Science (miscellaneous)

Publisher Institute of Electrical and Electronics Engineers Publication type

Journals

ISSN

21852766

Coverage

2010-ongoing

Scope

The ICIC Express Letters, Part B: Applications (abbreviated as ICIC-ELB) is a peer-reviewed English language journal of research and surveys on Innovative Computing, Information and Control, and is published by ICIC International monthly. The primary aim of the ICIC-ELB is to publish timely quality short papers (generally no more than 8 printing pages) with emphasis on applications of established or new developed novel techniques, approaches and

methodologies of computing systems, intelligent systems, information processing, and automation and control systems.

Homepage

How to publish in this journal Contact

Join the conversation about this journal

Enter Journal Title, ISSN or Publisher Name

Quartiles

The set of journals have been ranked according to their SJR and divided into four equal groups, four quartiles. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.

Category Year Quartile

Computer Science (miscellaneous) 2011 Q2 Computer Science (miscellaneous) 2012 Q2 Computer Science (miscellaneous) 2013 Q2 Computer Science (miscellaneous) 2014 Q3

SJR

The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scienti c in uence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scienti c in uence of the average article in a journal it expresses how central to the global

Citations per document

This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year.

The two years line is equivalent to journal impact factor

™ (Thomson Reuters) metric.

Cites per document Year Value

Cites / Doc. (4 years) 2010 0.000 Cites / Doc. (4 years) 2011 1.279

Total Cites Self-Cites

Evolution of the total number of citations and journal's

2011 2012 2013 2014 2015 2016 2017 2018

Computer Science (miscellaneous)

2011 2012 2013 2014 2015 2016 2017 2018 0

0.2 0.4

Ammar Altameemi 9 months ago

Great journal, it was my pleasure to deal with you.

reply

Elena Corera 9 months ago

Thank you very much for your comment!

Leave a comment

Cites / Doc. (4 years) 2013 0.485 Cites / Doc. (4 years) 2014 0.265 Cites / Doc. (4 years) 2015 0.206 Cites / Doc. (4 years) 2016 0.184 Cites / Doc. (4 years) 2017 0.113 Cites / Doc. (4 years) 2018 0.120

Journal Self-citation is de ned as the number of citation

from a journal citing article to articles published by the same journal.

Cites Year Value

S lf Cit 2010 0

External Cites per Doc Cites per Doc

Evolution of the number of total citation per document and external citation per document (i.e. journal self- citations removed) received by a journal's published documents during the three previous years. External citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents.

Cit Y V l

% International Collaboration

International Collaboration accounts for the articles that have been produced by researchers from several countries. The chart shows the ratio of a journal's documents signed by researchers from more than one country; that is including more than one country address.

Year International Collaboration

2010 11.63

2011 2 63

Citable documents Non-citable documents

Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. those documents other than research articles, reviews and conference papers.

Documents Year Value

N it bl d t 2010 0

Cited documents Uncited documents

Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those not cited during the following year.

Documents Year Value

Uncited documents 2010 0 Uncited documents 2011 16 Uncited documents 2012 155 Uncited documents 2013 391

← Show this widget in your own website

Just copy the code below and paste within your html code:

<a href="https://www.scimag

A

E

0 9 1.2 1.5

200

2010 2012 2014 2016 2018

0 0.7 1.4

2010 2012 2014 2016 2018

0 5 10 15

2010 2012 2014 2016 2018

0 600 1.2k

2010 2012 2014 2016 2018

0 600 1.2k

(will not be published)

Submit

The users of Scimago Journal & Country Rank have the possibility to dialogue through comments linked to a speci c journal. The purpose is to have a forum in which general doubts about the processes of publication in the journal, experiences and other issues derived from the publication of papers are resolved. For topics on particular articles, maintain the dialogue through the usual channels with your editor.

Developed by: Powered by:

Follow us on @ScimagoJR

Scimago Lab, Copyright 2007-2019. Data Source: Scopus®

I'm not a robot

reCAPTCHA Privacy - Terms