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A new feature extraction technique based on improved owl search algorithm: a case study in copper electrorefining plant

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Abstract

Feature extraction, feature clustering, feature selection are suitable to enhance learning performance, reduce computational complexity, create better generalizable models, and reduce required storage. Although there are several feature reduction techniques, still it remains one of the research hot spots in the field of data mining and machine learning groups. Owl search algorithm (OSA) is one of the recent metaheuristic optimization algorithms that mimic the hunting mechanism of owls in dark. However, OSA suffers from the same problem faced by many other optimization algorithms and tends to fall in local optima and premature convergence. To overcome these problems, two improvements for OSA algorithm are proposed in this paper. The first improvement uses a fuzzy system which is responsible to tune a control parameter in the updating phase of OSA. The second improvement includes the fuzzy system along with modifying the updating equation of OSA to enhance the exploration activity. In addition, this paper presents a new feature extraction technique for regression problems based on the improved OSA, called Fuzzy Owl Clustering Dimension Reduction (FOCDR). We apply a method that uses three weighting methods (i.e., soft, hard, and mixed) to extract new features based on the generated clusters. The experiment is divided into two parts. In the first part, the performance of the OSA algorithm and two improvement versions are analyzed with ten benchmark functions. The results show that the proposed versions on average can improve the convergence rate by 6.75% and 14.2% compared to OSA in solving complex problems. The second part is conducted to show FOCDR’s ability for feature selection problems. The effectiveness of FOCDR has been evaluated using four benchmark datasets and a real-world case study.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Shahid Bahonar University of Kerman, P.O. Box No 76135-133, Kerman, Iran

    Najme Mansouri & Behnam Mohammad Hasani Zade

  2. Department of Materials Science and Engineering, Shahid Bahonar University of Kerman, P.O. Box No 76135-133, Kerman, Iran

    Gholam Reza Khayati

  3. Senior Metallurgical Engineer, Process Control Unit, Khatoonabad Copper Refinery, Shahrebabak Copper Complex, National Iranian Copper Industries Company, Kerman, Iran

    Seyed Mohammad Javad Khorasani

  4. Research & Development Center, Shahrbabak Copper Complex, National Iranian Copper Industries Company, Kerman, Iran

    Roya Kafi Hernashki

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  1. Najme Mansouri

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  3. Behnam Mohammad Hasani Zade

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Appendices

Appendix 1

Mathematical of engineering problems.

Tension/compression spring design problem can be model as follows:

Consider

$$x = [x_{1} \,\,x_{2} \,\,x_{3} ] = [d\,\,D\,\,N]$$
$$Min\,f(x) = (x_{3} + 2)x_{2} x_{1}^{2}$$

Subject to

$$g_{1} (x) = 1 - \frac{{x_{2}^{3} x_{3} }}{{71785x_{1}^{4} }} \le 0$$
$$g_{2} (x) = \frac{{4x_{2}^{2} - x_{1} x_{2} }}{{12566(x_{2} x_{1}^{3} - x_{1}^{4} )}} + \frac{1}{{5108x_{1}^{2} }} - 1 \le 0$$
$$g_{3} (x) = 1 - \frac{{140.45x_{1} }}{{x_{2}^{2} x_{3} }} \le 0$$
$$g_{4} (x) = \frac{{x_{1} + x_{2} }}{1.5} - 1 \le 0$$

With\(0.05 \le x_{1} \le 2.0,\,0.25 \le x_{2} \le 1.3\), and\(2.0 \le x_{3} \le 15.0\)

Pressure vessel design problem can be model as follows:

$$Min\,f(x) = 0.6224x_{1} x_{3} x_{4} + 1.7781x_{2} x_{3}^{2} + 3.1661x_{1}^{2} x_{4} + 19.84x_{1}^{2} x_{3}$$

Subject to:

$$g_{1} (x) = - x_{1} + 0.0193x$$
$$g_{2} (x) = - x_{2} + 0.00954x_{3} \le 0$$
$$g_{3} (x) = - \pi x_{3}^{2} x_{4} - (4/3)\pi x_{3}^{3} + 1296000 \le 0$$
$$g_{4} (x) = x_{4} - 240 \le 0$$
$$0 \le x_{i} \le 100,\,\,i = 1,2$$
$$10 \le x_{i} \le 200,\,\,i = 3,4$$

Appendix 2

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Mansouri, N., Khayati, G.R., Mohammad Hasani Zade, B.et al. A new feature extraction technique based on improved owl search algorithm: a case study in copper electrorefining plant.Neural Comput & Applic34, 7749–7814 (2022). https://doi.org/10.1007/s00521-021-06881-z

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