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- 검색키워드
- 저자 : E. Hadavandi (검색결과 2 건)
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A modified binary version of aphid–ant mutualism for feature selection: a COVID-19 case study
Eslami N,Yazdani S,Mirzaei M,Hadavandi E 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.2
The speedy development of intelligent technologies and gadgets has led to a drastic increment of dimensions within the datasets in recent years. Dimension reduction algorithms, such as feature selection methods, are crucial to resolving this obstacle. Currently, metaheuristic algorithms have been extensively used in feature selection tasks due to their acceptable computational cost and performance. In this article, a binary-modified version of aphid–ant mutualism (AAM) called binary aphid–ant mutualism (BAAM) is introduced to solve the feature selection problems. Like AAM, in BAAM, the intensification and diversification mechanisms are modeled via the intercommunication of aphids with other colonies’ members, including aphids and ants. However, unlike AAM, the number of colonies’ members can change in each iteration based on the attraction power of their leaders. Moreover, the second- and third-best individuals can take the place of the ringleader and lead the pioneer colony. Also, to maintain the population diversity, prevent premature convergence, and facilitate information sharing between individuals of colonies including aphids and ants, a random cross-over operator is utilized in BAAM. The proposed BAAM is compared with five other feature selection algorithms using several evaluation metrics. Twelve medical and nine non-medical benchmark datasets with different numbers of features, instances, and classes from the University of California, Irvine and Arizona State University repositories are considered for all the experiments. Moreover, a coronavirus disease (COVID-19) dataset is used to validate the effectiveness of the BAAM in real-world applications. Based on the acquired outcomes, the proposed BAAM outperformed other comparative methods in terms of classification accuracy using various classifiers, including K nearest neighbor, kernel-based extreme learning machine, and multi-class support vector machine, choosing the most informative features, the best and mean fitness values and convergence speed in most cases. As an instance, in the COVID-19 dataset, BAAM achieved 96.53% average accuracy and selected the most informative feature subset.
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Study effects of conventional flotation reagents on bioleaching of zinc sulfide
M. Jafari,S. Chehreh Chelgani,S.Z. Shafaie,H. Abdollahi,E. Hadavandi 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.78 No.-
Althoughflotation and bio-extraction of metals from its products are extensively investigated, there arefew studied which evaluated the effects of reagents on bioleaching process. Both structure andconcentration offlotation reagents are effective factors on microorganism activities. In this study,Kendall’s tau (t) as a statistical method was used to statistically access the effect of typical sulfideflotation surfactants (collectors: potassium amyl-xanthate, potassium isobutyl-xanthate, sodium ethyl-xanthate, potassium isopropyl-xanthate, and Dithiophosphate), and frothers: pine oil and methylisobutyl carbinol) on the bioleaching of Zn sulfides in a mixed culture (Leptospirillum ferrooxidans,Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans). To consider both structure andconcentration of these reagents, their molarities were used for the statistical evaluations. The Kendallassessments indicated that by increasing in the molarity of reagents, the pH value (the most effectivefactors of bioleaching) was increased (t: 0.56) while the ORP value (t:0.54), Fe3þFe2þ ratio (t:0.51) andnumbers of oxidizing bacteria (t:0.38) in the solution were decreased. Therefore, as a result of thesemulti-interactions, by increasing the molarity of reagents, Zn recovery was decreased (t:0.45). Theseresults potentially can be used for selection offlotation reagents when bioleaching would be themetallurgical metal extraction method.
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