Applied Mathematics and Nonlinear Sciences, Journal Year: 2025, Volume and Issue: 10(1)
Published: Jan. 1, 2025
Abstract Ancestral genome reconstruction is a critical area of research for understanding evolutionary processes and genomic adaptations. This study presents novel evaluation framework leveraging the Improved Whale Optimization Algorithm-Deep Belief Network (IWOA-DBN) to assess performance ancestral reconstruction. As algorithm, IWOA algorithm enhances optimization initial parameters DBN by integrating advanced techniques such as nonlinear convergence mechanisms, chaotic disturbance, improved population diversity strategies. These enhancements improve DBN's ability process complex data extract deep features, ensuring more accurate reliable evaluations. The IWOA-DBN model combines robust feature learning capabilities Deep Networks with adaptive strengths IWOA, forming comprehensive solution analyzing outcomes. Systematic experiments were conducted evaluate accuracy computational efficiency proposed method compared traditional approaches. results demonstrate that significantly improves reliability precision evaluations, highlighting its potential powerful tool structures relationships. work provides an effective strategy addressing challenges using artificial intelligence techniques.
Language: Английский