Classical crisp decision trees (DT) are widely applied to classiication tasks. Nevertheless, there are still a lot of problems especially when dealing with numerical (continuous-valued) attributes. Some of those problems can be solved using fuzzy decision trees (FDT). This paper proposes a method for handling continuous-valued attributes with automatically generated (as opposed to user deened) ...

In recent years, Cloud computing has been developed and become the foundation of a wide range applications. It allows users to access catalog standardized services respond their business needs flexibly adaptively, in event unforeseen demands, paying solely for consumption they have made. Task scheduling problem is considered one most critical cloud challenges. The refers how reasonably order al...

With the advent of new technologies in medical field, huge amounts cancerous data have been collected and are readily accessible to research community. Over years, researchers employed advanced mining machine learning techniques develop better models that can analyze datasets extract conceived patterns, ideas, hidden knowledge. The mined information be used as a support decision making for diag...

The development of renewable-energy-based microgrids is being considered as a potential solution to lessen the unrelenting burden on centralized utility grid. Furthermore, recent studies reveal that integrated multi-microgrid cluster systems developed in urban communities maximize effectiveness and greatly decrease grid dependence. However, due uncertain nature renewable energy sources frequent...

The decisions on the project delivery method when conducting a construction project are an important part of the process and can heavily influence the success or failure of the project. Many factors have to be considered, however, in determining the project delivery method, and there are no definite criteria. This ambiguity can cause much difficulty. As such, this paper proposes a system based ...

This paper presents an Intrusion Detection System (IDS) with the integration of multi agent systems and artificial intelligence techniques such as fuzzy logic controller (FLC), multi-layer perceptron (MLP) and adaptive neurofuzzy inference system (ANFIS). The paper introduces Network Intrusion Detection Systems (NIDS), which monitors the network traffic and detect any possible attacks. The syst...

BACKGROUND Breast cancer is one of the most critical cancers and is a major cause of cancer death among women. It is essential to know the survivability of the patients in order to ease the decision making process regarding medical treatment and financial preparation. Recently, the breast cancer data sets have been imbalanced (i.e., the number of survival patients outnumbers the number of non-s...

Recently by developing the technology, the number of network-based servicesis increasing, and sensitive information of users is shared through the Internet.Accordingly, large-scale malicious attacks on computer networks could causesevere disruption to network services so cybersecurity turns to a major concern fornetworks. An intrusion detection system (IDS) could be cons...

Soil mapping is a permanent demand, but the traditional method does not allow fast execution and low cost. Digital soil (DSM) aims to improve process by working with models that treat spatial variability quantitatively. In this perspective, objective of study perform DSM Parnaíba River Delta, Northeastern Brazil, through decision tree (DT) integration technique using set attributes derived from...

Neural network tree (NNTree) is a hybrid learning model with the overall structure being a decision tree (DT), and each non-terminal node containing an expert neural network (ENN). Generally speaking, NNTrees outperform conventional DTs because better features can be extracted by the ENNs, and the performance can be improved further through incremental learning. In addition, as we have shown re...