Teaching-learning-based optimization (TLBO) algorithm is a novel heuristic method which simulates the teaching-learning phenomenon of a classroom. However, in the later period of evolution of the TLBO algorithm, the lower exploitation ability and the smaller scope of solutions led to the poor results. To address this issue, this paper proposes a novel version of TLBO that is augmented with error correction strategy and Cauchy distribution (ECTLBO) in which Cauchy distribution is utilized to expand the searching space and error correction to avoid detours to achieve more accurate solutions. The experimental results verify that the ECTLBO algorithm has overall better performance than various versions of TLBO and is very competitive with respect to other nine original intelligence optimization algorithms. Finally, the ECTLBO algorithm is also applied to path planning of unmanned aerial vehicle (UAV), and the promising results show the applicability of the ECTLBO algorithm for problem-solving.

The leakage point location of the water supply pipeline (WSP) can be estimated by the time difference of the leakage-characteristic signals obtained from both ends of the pipeline. It is very important to extract the characteristic signal in the frequency-domain to accurately locate the leakage point. The variational mode decomposition (VMD) has been proven to be effective in extracting leakage-characteristic frequency-domain signals, but it needs to set parameters in advance to adjust the signal processing effect. Therefore, it is proposed to initialize the center frequency required for the VMD with the frequency corresponding to the peak of the power spectrum of the original signal and then solve the preset problem of VMD decomposition layers by the recursive method. In addition, mutual information is used as a screening criterion for composite pattern functions to select appropriate pattern components to reconstruct signals. The actual leak location results show that the location errors of the proposed algorithm are only 0.20 and 1.66% for 23.3 and 38.9 m pipeline lengths, respectively. This shows that the proposed method can achieve the accurate location of the water leakage point under long measurement distances and complex interference.

No abstract