A novel method for image thresholding using interval type-2 fuzzy set and Bat algorithm

IDEFE algorithm: IDE algorithm optimizes the fuzzy entropy for the gland segmentation

Breast cancer occurs in the epithelial tissue of the gland, so the accuracy of gland segmentation is crucial to the physician's diagnosis. An innovative technique for breast mammography image gland segmentation is put forth in this paper. In the first step, the algorithm designed the gland segmentation evaluation function. Then a new mutation strategy is established, and the adaptive controlled variables are used to balance the ability of improved differential evolution (IDE) in terms of investigation and convergence. To evaluate its performance, The proposed method is validated on a number of benchmark breast images, including four types of glands from the Quanzhou First Hospital, Fujian, China. Furthermore, the proposed algorithm is been systematically compared to five state-of-the-art algorithms. From the average MSSIM and boxplot, the evidence suggests that the mutation strategy may be effective in searching the topography of the segmented gland problem. The experiment results demonstrated that the proposed method has the best gland segmentation results compared to other algorithms.

Curative effect of pop light music on depression patients based on improved fuzzy algorithm

With the aggravation of many social psychological and psychological stress factors, the high incidence rate of depression and depression has become a major problem which puzzles people’s health and even endangers life. Non drug therapy has become an effective alternative to drug therapy, which is in line with the new trend of natural medicine in the world. This paper will use the real world research method (RWS) to conduct a clinical trial of pop light music in the treatment of depression. Based on the fuzzy algorithm, a comprehensive evaluation system for the treatment of depression was established. By comparing and analyzing the main efficacy indexes between music group and traditional medicine group, we found that the cure rate, clinical control rate, significant efficiency, effective rate and ineffective rate of music therapy group were significantly better than those of drug group. Through the analysis of seven factors of HAMD (Hamilton Depression Scale) scale, we found that pop light music can improve the sleep status and physical symptoms of patients, and the improvement degree of music therapy is significantly better than that of drug therapy.

Renyi’s Entropy Based Multilevel Thresholding Using a Novel Meta-Heuristics Algorithm

Multi-level image thresholding is the most direct and effective method for image segmentation, which is a key step for image analysis and computer vision, however, as the number of threshold values increases, exhaustive search does not work efficiently and effectively and evolutionary algorithms often fall into a local optimal solution. In the paper, a meta-heuristics algorithm based on the breeding mechanism of Chinese hybrid rice is proposed to seek the optimal multi-level thresholds for image segmentation and Renyi’s entropy is utilized as the fitness function. Experiments have been run on four scanning electron microscope images of cement and four standard images, moreover, it is compared with other six classical and novel evolutionary algorithms: genetic algorithm, particle swarm optimization algorithm, differential evolution algorithm, ant lion optimization algorithm, whale optimization algorithm, and salp swarm algorithm. Meanwhile, some indicators, including the average fitness values, standard deviation, peak signal to noise ratio, and structural similarity index are used as evaluation criteria in the experiments. The experimental results show that the proposed method prevails over the other algorithms involved in the paper on most indicators and it can segment cement scanning electron microscope image effectively.

Indoor three-dimensional high-precision positioning system with bat algorithm based on visible light communication

A three-dimensional (3-D) positioning system on the basis of bat algorithm (BA) using visible light communication is proposed in this work. BA is a global optimization algorithm that can be used to solve the indoor positioning problem. In BA, the positioning process is considered to be a process of searching for the receiver by many bats in an indoor space of 3  m×3  m×4  m. Therefore, taking advantage of the bat search algorithm, 3-D low-complexity and high-precision indoor positioning is able to be actualized when the number of iterations reaches a certain condition. The simulation results show that the system can achieve high-precision positioning at different signal-to-noise ratios. Meanwhile, a trajectory tracking experiment is carried out to validate the good performance of this positioning system. The proposed algorithm is a positioning method with good potential in various positioning applications.