Abstract
The Inclined Planes System Optimization (IPO) algorithm is recent algorithm that uses Newton's second law to perform optimization. After conducting a thorough literature review, this paper proposes an improved version of IPO called IIPO. This improvement is achieved by changing exploratory and exploitative behavior of the standard IPO proportional to the progress of optimization (iteration). The IIPO is employed for optimizing IIR digital filter design, which is a challenging engineering problem. Adaptive IIR modeling as a multimodal optimization problem is designed and developed under system identification structure with an appropriate single-objective function in the frequency domain. Implementations are performed in both modeling cases with same and reduced orders, and under two identification forms with and without environmental additive noise. The results are reported along with various analyzes compared to a wide range of IPO variants. The statistical results on 100 independent trials show a success of more than 90% of cases, the proposed IIPO algorithm substantially outperforms other comparative algorithms in terms of accuracy of estimated coefficients, convergence, fitness, output responses, noise analysis, stability, and reliability.1
| Original language | English |
|---|---|
| Article number | 117127 |
| Journal | Expert Systems with Applications |
| Volume | 200 |
| DOIs | |
| Publication status | Published - 15 Aug 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
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SDG 12 Responsible Consumption and Production
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SDG 13 Climate Action
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SDG 17 Partnerships for the Goals
Keywords
- Adaptive system identification
- IIR filter
- Inclined planes system optimization
- Multimodal design problems
- State-of-the-art versions
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