−Segmentation is a difficult and challenging problem in the magnetic resonance images, and it considered as important in computer vision and artificial intelligence. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. In this paper, we present a novel FCM algorithm for weighted bias (also called intensity in-...

Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. Clustering is a primary data description method in data mining which group’s most similar data. The data clustering is an important problem in a wide variety of fields. Including data mining, pattern recognition, and bioinformatics. It aims to organize a collection of data items into...

Dalam upaya mencapai kesejahteraan Indonesia, salah satu kebijakan Pemerintah yang akan dilaksanakan adalah penyelenggaraan dan pelaksanaan program transmigrasi. Pada Umumnya transmigrasi ditawarkan oleh kepada semua masyarakat tanpa mengetahui latar belakang ekonomi keluarganya sehingga tidak tepat sasaran. Berdasarkan masalah dalam penelitian ini bagaimana cara merancang, membangun, mengemban...

Vehicle Routing Problem (VRP) has been an interesting research area since its introduction. There are various types of VRP models and different solution techniques proposed for this problem. This paper uses several clustering algorithms in initialization of Simulated Annealing to solve VRP. The main contribution of this research is to assess the effect of using some clustering methods in buildi...

An efficient noise reduction approach is proposed by combining Robust Outlyingness Ratio (ROR) which measures how impulse like each pixel is, with noise adaptive fuzzy switching median filter (NAFSM) and fuzzy c-means (FCM) segmentation. Based on the ROR values all the pixels are divided into four levels. Then in the coarse and fine stage introduce the NAFSM filter that optimizes the performanc...

Clustering on target positions is a class of centralized algorithms used to calculate the surveillance robots' displacements in Cooperative Target Observation (CTO) problem. This work proposes and evaluates Fuzzy C-means (FCM) Density-Based Spatial Applications with Noise (DBSCAN) K-means (DBSk) based self-tuning clustering for CTO problem compares its performances that K-means. Two random moti...

In this study, a biomedical diagnosis system for pattern recognition with normal and abnormal classes has been developed. First, feature extraction processing was made by using the Doppler Ultrasound. During feature extraction stage, Wavelet transforms and shorttime Fourier transform were used. As next step, wavelet entropy were applied to these features. In the classification stage, hidden Mar...

Pixel classification among overlapping land cover regions in remote sensing imagery is a challenging task. Detection of uncertainty and vagueness are always key features for classifying mixed pixels. This chapter proposes an approach for pixel classification using hybrid approach of Fuzzy C-Means and Particle Swarm Optimization methods. This new unsupervised algorithm is able to identify cluste...