The spatial and temporal distribution of land cover is a fundamental dataset for urban
ecological research. An expert (or hypothesis testing) system has been used with Landsat …

In this paper, a multi-agent classifier system with Q-learning is proposed for tackling data
classification problems. A trust measurement using a combination of Q-learning and …

Land use change becomes one of the significant issues for planners and decision makers in
urban and regional policy. Data, information, and tool sometimes turn to be a burden in the …

The development and implementation of green product certification have created new
requirements for risk assessment of the certification process. Conventional methods of …

The single-layer perceptron with single output node is a well-known neural network for two-
class classification problems. Furthermore, the sigmoid or logistic function is usually used as …

The classification ability of a single-layer perceptron could be improved by considering
some enhanced features. In particular, this form of neural networks is called a functional-link …

A novel Self-Organizing Neuro-Fuzzy Multilayered Classifier, the GA-SONeFMUC model, is
proposed in this paper for land cover classification of multispectral images. The model is …

This review paper discusses recent developments in soft computing techniques and
applications specific to remote sensing, especially in the last two decades. Even though, the …

The main objective of this study is to generate a knowledge base which is composed of user-
defined variables and included raster imagery, vector coverage, spatial models, external …

A multi-layer perceptron with single output node can be served as a classifier for two-class
problems. Traditionally, an activation function such as the sigmoid function of a neuron …