Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting

Guangjin Zhang; Kevin Kam Fung Yuen

doi:10.1016/j.procs.2013.05.057

Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting

Guangjin Zhang
, Kevin Kam Fung Yuen

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

5 Citations (Scopus)

Abstract

Forecasting by artificial neural network is a popular approach in recent years. This paper proposes a new hybrid approach PCNP-PSONN which combines the Primitive Cognitive Network Process (PCNP) and Particle Swarm Optimization Neural Network (PSONN) for forecasting. PCNP is a rectified approach of the Analytic Hierarchy Process (AHP), to quantify the influence of factors, whilst Particle Swarm Optimization has been used for optimizing the neural network by improving the learning efficiency. The combination of PCNP and PSONN, PCNP-PSONN, can increase accuracy of network through selection of high influenced factors.

Original language	English
Title of host publication	First International Conference on Information Technology and Quantitative Management
Publisher	Elsevier
Pages	441-448
Number of pages	8
DOIs	https://doi.org/10.1016/j.procs.2013.05.057
Publication status	Published - 2013
Externally published	Yes
Event	International Conference on Information Technology and Quantitative Management (ITQM) 2013 - Suzhou, China Duration: 16 May 2013 → 18 May 2013 Conference number: 1st

Publication series

Name	Procedia Computer Science
Volume	17
ISSN (Print)	1877-0509

Conference

Conference	International Conference on Information Technology and Quantitative Management (ITQM) 2013
Abbreviated title	ITQM 2013
Country/Territory	China
City	Suzhou
Period	16/05/13 → 18/05/13

Keywords

Forecasting
Particle Swarm Optimization Neural Network
Primitive Cognitive Network Process

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10.1016/j.procs.2013.05.057Licence: CC BY-NC-ND

Cite this

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title = "Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting",

abstract = "Forecasting by artificial neural network is a popular approach in recent years. This paper proposes a new hybrid approach PCNP-PSONN which combines the Primitive Cognitive Network Process (PCNP) and Particle Swarm Optimization Neural Network (PSONN) for forecasting. PCNP is a rectified approach of the Analytic Hierarchy Process (AHP), to quantify the influence of factors, whilst Particle Swarm Optimization has been used for optimizing the neural network by improving the learning efficiency. The combination of PCNP and PSONN, PCNP-PSONN, can increase accuracy of network through selection of high influenced factors.",

keywords = "Forecasting, Particle Swarm Optimization Neural Network, Primitive Cognitive Network Process",

author = "Guangjin Zhang and Yuen, \{Kevin Kam Fung\}",

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doi = "10.1016/j.procs.2013.05.057",

language = "English",

series = "Procedia Computer Science",

publisher = "Elsevier",

pages = "441--448",

booktitle = "First International Conference on Information Technology and Quantitative Management",

address = "Netherlands",

note = "International Conference on Information Technology and Quantitative Management (ITQM) 2013, ITQM 2013 ; Conference date: 16-05-2013 Through 18-05-2013",

}

Zhang, G & Yuen, KKF 2013, Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting. in First International Conference on Information Technology and Quantitative Management. Procedia Computer Science, vol. 17, Elsevier, pp. 441-448, International Conference on Information Technology and Quantitative Management (ITQM) 2013, Suzhou, China, 16/05/13. https://doi.org/10.1016/j.procs.2013.05.057

Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting. / Zhang, Guangjin; Yuen, Kevin Kam Fung.
First International Conference on Information Technology and Quantitative Management. Elsevier, 2013. p. 441-448 (Procedia Computer Science; Vol. 17).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

TY - GEN

T1 - Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting

AU - Zhang, Guangjin

AU - Yuen, Kevin Kam Fung

N1 - Conference code: 1st

PY - 2013

Y1 - 2013

N2 - Forecasting by artificial neural network is a popular approach in recent years. This paper proposes a new hybrid approach PCNP-PSONN which combines the Primitive Cognitive Network Process (PCNP) and Particle Swarm Optimization Neural Network (PSONN) for forecasting. PCNP is a rectified approach of the Analytic Hierarchy Process (AHP), to quantify the influence of factors, whilst Particle Swarm Optimization has been used for optimizing the neural network by improving the learning efficiency. The combination of PCNP and PSONN, PCNP-PSONN, can increase accuracy of network through selection of high influenced factors.

AB - Forecasting by artificial neural network is a popular approach in recent years. This paper proposes a new hybrid approach PCNP-PSONN which combines the Primitive Cognitive Network Process (PCNP) and Particle Swarm Optimization Neural Network (PSONN) for forecasting. PCNP is a rectified approach of the Analytic Hierarchy Process (AHP), to quantify the influence of factors, whilst Particle Swarm Optimization has been used for optimizing the neural network by improving the learning efficiency. The combination of PCNP and PSONN, PCNP-PSONN, can increase accuracy of network through selection of high influenced factors.

KW - Forecasting

KW - Particle Swarm Optimization Neural Network

KW - Primitive Cognitive Network Process

UR - https://www.scopus.com/pages/publications/84895813212

U2 - 10.1016/j.procs.2013.05.057

DO - 10.1016/j.procs.2013.05.057

M3 - Conference Paper

AN - SCOPUS:84895813212

T3 - Procedia Computer Science

SP - 441

EP - 448

BT - First International Conference on Information Technology and Quantitative Management

PB - Elsevier

T2 - International Conference on Information Technology and Quantitative Management (ITQM) 2013

Y2 - 16 May 2013 through 18 May 2013

ER -

Toward a hybrid approach of primitive cognitive network process and particle swarm optimization neural network for forecasting

Abstract

Publication series

Conference

Keywords

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