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Online transaction failures often show up as "500: Internal Server Error" in web server access logs. In many instances determining the root cause of the failure is a difficult task. It could either be a bug associated with a specific HTTP request alone or the result of an undesirable state created by previous HTTP transactions. The latter case, which we call workload dependent faults, are...
This paper presents the results of the application of a Genetic Algorithm (GA) to predict path loss for urban areas for Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE — A) networks at 879 MHz using empirical propagation models. We conducted a comparative test, where simulated Free Space and Ericsson 9999 models along with their optimized versions were compared with experimental data...
Species distribution modeling (SDM) calculates a species’ probabilistic distribution by combining Environmental raster layers with species datasets. Such models can help to answer complex questions in Ecology/Biology/Health, e.g., by calculating impacts of climate changes in Biodiversity, or the potential for a disease spread (vectors’ modeling). Machine learning is largely applied in SDM, being the...
The process of modeling of a real system usually implies an iterative approach where an initial model is incrementally modified in order to increase its accuracy with regard to available experimental data. Many approaches are discussed in the literature, among which some are based on Artificial Intelligence techniques. Continuous improvement in the mathematical model adequacy is very similar with...
The advancement of information technology and research in finance have recently led to flash decision making and actions by computer algorithms in order to respond to fast events occurring in the stock markets. This new area of technology involves the implementation of high-speed trading strategies which have generated significant amount of activity and information for financial research. In this...
Creating new software or software-intensive systems is still a challenge and far removed from a traditional engineering domain. The increasing size of software deployed in typical systems and the emergence of very large highly distributed systems necessitates additional techniques to assure the systems quality. Using the example of the German automatic toll system we briefly outline a simulation driven...
An Agent Based Model (ABM) is a powerful tool for its ability to represent heterogeneous agents which through their interactions can reveal emergent phenomena. For this to occur though, the set of agents in an ABM has to accurately model a real world population to reflect its heterogeneity. But when studying human behavior in less well developed settings, the availability of the real population data...
This paper proposes a Double Seasonal Holt-Winters (DSHW) forecasting model with an auxiliary Artificial Neural Network (ANN) trained with a Genetic Algorithm (GA) to model the DSHW residuals. ANN complements and improves the DSHW prediction. The proposed model also includes an on-line validation and reconstruction mechanism useful to detect and correct missing and erroneous data. This mechanism also...
In the paper the novel feature selection method, using wrapper model and ensemble approach, is presented. In the proposed method features are selected dynamically, i.e. separately for each classified object. First, a set of identical one-feature classifiers using different single feature is created and next the ensemble of features (classifiers) is selected as a solution of optimization problem using...
The paper presents a novel hybrid searching COMBI GMDH-GA algorithm with GA used to discover model of optimal structure quickly because of avoiding exhaustive search. The obtained experimental results demonstrate that this algorithm performs well when solving inductive modelling tasks, both artificial and real-world.
Advanced process control techniques use at some point a model of the process that is controlled. In real industrial processes, usually there are present nonlinearities, the time changing parameters of the equipment, noise and uncertainties. These processes are sometimes modeled by NARMAX models. The current paper approaches system modeling with NARMAX polynomials of a distillation process with the...
In this research work, it is tried to develop a technique for ‘Credit Card Fraud Detection’. Credit Card can be accepted for each online and offline in today's world. There are combinations of methods used. Firstly, Shopping Behavior is based on which type of products customer buys. Secondly, Spending Behavior in this the fraud is detected based on the maximum amount spent. Thirdly, Hidden Markov...
The aim of this paper is to propose a general methodology to improve the linguistic-accuracy trade-off of fuzzy models, applicable to any rule-based fuzzy model. Here, the neuro-fuzzy system FasArt (Fuzzy Adaptive System ART based) is used to obtain rule-based fuzzy models, as shown in previous papers and works. FasArt, however, has the usual drawbacks, from the linguistic point of view, of most (precise)...
ABC analysis is an inventory management technique used to classify inventory items into three predefined and ordered categories A, B and C: Category A contains items with the highest impact for the company, while the category C contains items with the lowest impact. The aim of this classification technique is to keep related inventory costs under control. According to the ABC analysis, the classification...
This paper presents a multi-objective portfolio selection model solved using genetic algorithms. In this approach an entropy measure has been added so that a well-diversified portfolio is generated. Based on literature survey, it was observed that there is a need of new portfolio selection model which is free from the limitations as observed in existing models. Hence emphasis has been put on proposing...
In public Infrastructure-as-a-Service (IaaS), virtual machines, servers, storage, and network are provided by cloud service providers. As a cloud service provider, who is facing a task for time constraint, how to schedule the service resources to achieve the lowest cost becomes more and more important. Recently, most of works about MapReduce task scheduling are focus on homogeneous MapReduce framework...
According to the rough set theory, this paper introduced a neuro-rough model and extends this to a probabilistic domain using a Bayesian framework, trained using a Markov Chain Monte Carlo simulation and the Metropolis algorithms. Firstly, rough set theory was presented, including the granulation of rough set membership function, the network weight formula of probability and rough set formulation...
Evolutionary approach is used in this research to adjust the structure of a human limb model and select the parameters related to the data acquisition. Portable device used to supervise therapeutic exercises imposes restrictions on the computational complexity allowed to model patient's limbs which in turn narrows the choice of possible modeling techniques. While neural networks based models possess...
One of the key success factors of lending organizations in general and banks in particular is the assessment of borrower credit worthiness in advance during the credit evaluation process. Credit scoring models have been applied by many researchers to improve the process of assessing credit worthiness by differentiating between prospective loans on the basis of the likelihood of repayment. Thus, credit...
Directional and stream data are common in many research fields. Wind speed and direction are the most important variables for effective wind energy utilization. It is also well known, that wind significantly influences the current-carrying capacity of overhead power transmission lines. This shows the importance of knowing the annual wind direction distribution for specific locations, e.g. where wind...
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