The International Seminar on Mathematics in Industry (ISMI) and the International Conference on Theoretical and Applied Statistics (ICTAS), ISMI-ICTAS18. Rate each aspect of the summary on a scale of 1 to 5, where 1 is very bad and 5 is the best. If certain aspects in particular abstractly do not apply, mark as NA (not applicable).
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2) …the big problem with the air pollution data …the real problem with the air pollution data. On behalf of the organizing committee, I would like to take this opportunity to thank you for your support of ISMI-ICTAS18. International Seminar on Mathematics in Industry & International Conference on Theoretical and Applied Statistics 2018 (ISMI-ICTAS18).
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Reviewer's confidence
Title: Particle swarm optimization for obtaining the weights of neural networks Authors: Budi Warsito, Hasbi Yasin, Alan Prahutama. Check one box for the score and provide a detailed summary, including a justification for your scores. In general, the article is not suitable to be presented as a journal article, but can be accepted as a conference report.
Several studies have been reported on the use of PSO to determine weights of NN, so how different is the study compared to the literature. Phases in the study must be clearly presented so that the study can be repeated by others. The purpose of the experiments was not detailed - why is it necessary to compare the activation functions.
The final weights obtained by PSO are not presented, although the title of the article is about weight determination. Flowchart of the integration between PSO and NN would be much appreciated in this article. Subject: Re: SOFT REMNIDER: [CHANGES] revised manuscript ID-1192 submitted to MATHEMATICS To: budi warsito
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SOFT REMNIDER : [AMENDMENTS] revised manuscript ID-1192 submitted to MATEMATIKA
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In this case, Feed Forward Neural Network (FFNN) is the chosen class of the network architecture. The heuristic algorithm determined for obtaining the weights of the network is Particle Swarm Optimization (PSO). The eight architecture was performed to improve the accuracy of the neural network model.
Performance comparison of different architectures based on minimum MSE and stability of results is presented in this paper. The construction of the network architecture is also very flexible, so that there are many possibilities for advanced investigations. Some of the flexibility is the input selection procedure, the determination of the number of hidden units, the selection of the activation function.
In the past many years, rapid progress has been made in predicting the concentration of air pollutants. In the processing of updating the speed and position of the particles, the inertia weights are always updated in each iteration. The determination of the fitness value at the initial position of the PSO particles is very important.
The length of the data is 120 and divided into two parts, the first 100 data as training and the remaining 20 as testing. Significant correlation values were lagged values as input candidates. The result of a good in-sample prediction in a given architecture does not guarantee a good out-of-sample prediction.
To determine the correctness of the forecast, a comparison of the actual data and the forecast result in one of the experiments is indicated. It can be seen from the forecast pattern that it follows the actual pattern. In the NN-PSO prediction model, as in this research, the choice of network parameters affects the performance of the system.
Particle Swarm Optimization”, Proceedings of the IEEE International Conference on Neural Networks, Piscataway, NJ, USA. Please be informed that the ISMI-ICTAS18 organizer will pay the article processing fee for the manuscript presented at the International Seminar on Mathematics in Industry & International Conference on Theoretical and Applied Statistics (ISMI-ICTAS18) which has been accepted for publication in MATHEMATICS : Malaysian Journal of Industrial and Applied Mathematics Serial number.
PAYMENT FOR ARTICLE PROCESSING FEE] MATEMATIKA: Editor Decision on Manuscript ID 1213
The editors and they will issue an invoice to Bendahari ISMI-ICTAS18 to proceed with the payment. MATHEMATICS: Malaysian Journal of Industrial and Applied Mathematics UTM Center for Industrial and Applied Mathematics (UTM-CIAM). 27/1/2021 Gmail - [PAYMENT FOR ARTICLE PROCESSING FEE] MATHEMATICS: Editor Decision on Manuscript ID 1213 Email: [email protected] / [email protected].
Subject: MATHEMATICS: Editor's decision on manuscript ID 1213 To: Budi Warsito
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