This paper constructed a robust methodology to investigate the impact of news regarding macroeconomic policies on exchange rate fluctuations, and examined applicability qualitative information alongside historical data predict rates. To do so, hybrid machine learning algorithms comprised natural language processing, fuzzy logic, support vector regression have been constructed. study emphasizes ...

Additive manufacturing (AM), as a fast-developing technology for rapid manufacturing, offers paradigm shift in terms of process flexibility and product customisation, showing great potential widespread adoption the industry. In recent years, energy consumption has increasingly attracted attention both academia industry due to increasing demands applications AM systems production. However, are c...

Abstract Reinforcement learning (RL) techniques nurture building up solutions for sequential decision-making problems under uncertainty and ambiguity. RL has agents with a reward function that interacts dynamic environment to find out an optimal policy. There are associated like the should be specified in advance, design difficulties unable handle large complex problems, etc. This led developme...

Various sentiment analysis methods have been proposed to obtain reviewing opinions from machine learning and vocabulary-based sentiment. In previous research using only methods, I got an unsatisfactory accuracy score because a lexical / lexicon hybrid method was used in this study. Machine is that can improve the performance of existing analysis. With proposal researcher able experimental resul...

One of the severe health problems and most common types heart disease (HD) is Coronary (CHD). Due to lack a healthy lifestyle, HD would cause frequent mortality worldwide. If attack occurs without any symptoms, it cannot be cured by an intelligent detection system. An effective diagnosis CHD should prevent human casualties. Moreover, systems employ clinical-based decision support approaches ass...

Learned models of behavior have the disadvantage that they must be retrained after any change in system configuration. Autonomic management methods based upon learned models lose effectiveness during the retraining period. We propose a hybrid approach to autonomic resource management that combines management based upon learned models with “highly-reactive” management that does not depend upon l...

Attacks against computer networks are evolving rapidly. Conventional intrusion detection system based on pattern matching and static signatures have a significant limitation since the signature database should be updated frequently. The unsupervised learning algorithm can overcome this limitation. Ant Clustering Algorithm (ACA) is a popular unsupervised learning algorithm to classify data into ...

Modelling problems containing a mixture of Boolean and numerical variables is a long-standing interest of Artificial Intelligence. However, performing inference and learning in hybrid domains is a particularly daunting task. The ability to model this kind of domains is crucial in “learning to design” tasks, that is, learning applications where the goal is to learn from examples how to perform a...

the aim of this study was to compare three approaches of medical parasitological course. this cross sectional study carried out in 94 medical and pharmacy students. lecturer based learning, problem based learning, and combined approaches were used for teaching the parasitological course. kappa and spss16 were used to analysis. 82.9% of students were interested in lecturer based learning, 64.9% ...