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The demand of text classification is growing significantly in web searching, data mining, web ranking, recommendation systems and so many other fields of information and technology. This paper illustrates the text classification process on different dataset using some standard supervised machine learning techniques. Text documents can be classified through various kinds of classifiers. Labeled text...
This paper presents a user authentication system based on mouse movement data. An available logging tool named Recording User Input (RUI) is used to collect three types of mouse actions — Mouse Move, Point-and-Click on Left or Right mouse button and Drag-and-Drop. Collected data are divided into N-number of blocks consisting of specific number of actions. From each block seventy four features are...
This paper presents Artificial Neural Network (ANN) technique for predicting the output power from Grid-Connected Photovoltaic (GCPV) system. Different inputs are utilized in several models of ANN in order to obtain the output power. ANN parameters are chosen using trial-and-error method to find the optimal value of root mean square error (RMSE), mean absolute percentage error (MAPE) and correlation...
The cost of deleting a software bug increases ten times as it is floated onto the next phase of software development lifecycle (SDLC). This makes the task of the project managers difficult and also degrades the quality of the output software product. Software defect prediction (SDP) was proposed as a solution to the problem which could anticipate the defective modules and hence, deal with them in...
The flood can cause wide destroy to property and life because of the supreme corrosive force and can be highly damaging. In order to decrease the damages cause by the flood, an Artificial Neural Network (ANN) model has been established to predict flood in Sungai Isap, Kuantan, Pahang, Malaysia. This model is able to imitate same as the brain thinking process and avoid any influence to the predict...
Weather forecasting is the application of science and technology in order to predict the weather conditions. It is important for agricultural and industrial sectors. Models of Artificial Neural Networks with supervised learning paradigm are suitable for weather forecasting in complexity atmosphere. Training algorithm is required for providing weight and bias values to the model. This research proposed...
This work attempts to find the most optimal setting for shallow artificial neural network (ANN) for Bengali digit dataset. Recognition of handwritten Bengali numerals has recently gained much interest among researchers due to significant performance gain found in the recognition of English numerals using artificial neural network. In this work, a new dataset of 70,000 samples were created first by...
This paper presents the development of a neuromorphic system for visual pattern recognition. Associative memory algorithm has been used to recognize specific patterns and the method is implemented with discrete circuit elements that use memristors as the synapse. Weight of the synapses between the inputs and output neurons are adjusted by memristors. The amount of the neural block depends on how many...
The increasing penetration of renewable generation brings a significant escalation of intermittency to the power and energy system. This variability requires a new degree of flexibility from the whole system. The active participation of small and medium players becomes essential in this context. This is only possible by using adequate forecasting techniques applied both to the consumption and to generation...
Sign language is the only means of communication for deaf and dump people which uses manual communication and body language to convey meaning. For any sign language, an interpreter is essential to communicate with deaf and dump people. To enhance interaction with community, Sign Language Recognition (SLR) is a growing field of research now a days. The task of SLR is language specific and a number...
Microcalcifications are tiny calcium accumulations in the breast and are a warning sign of possible breast carcinoma in the early stages of its formation, so it is highly important for radiologists to identify them in a digital mammography and also to be able to discern in which category of BIRADS they belong. In this study the focus is to classify into BIRADS 2, 3 and 4, categories in which the advance...
Artificial neural networks (ANN) are one of the dominant learning techniques used in the field of artificial intelligence and have significant assets as their properties imitate the behavior of neurons in human brain. In this paper is presented the research focused on ANN, specifically Multilayer perceptron (MPL) with the aim of detection of human face in the still image. This system was implemented...
The paper proposes a new method based on artificial neural network (ANN) for estimation of pressure loss coefficients in Tee Junction for dividing flows. The selected features are given as input to the ANN including flow and geometry parameters of Tee Junction for training and pressure loss coefficients are estimated in an efficient manner. The paper also gives comparison results of ANN based approach...
An accurate forecasting of PV output is essential to improve real-time control performance and to reduce possible negative impacts. For an energy management system (EMS) of distributed energy resources, accurate forecasting of solar irradiation and thus PV power output can reduce the impact of uncertainty for PV power generation, improve system reliability, and increase the penetration level of the...
Artificial Neural Network (ANN) is a nonlinear signal processing devices and works based on human brain principles. It is one of the most widely used techniques for forecasting and predicting. In this work, ANN is used to model baseline electrical energy use for a chiller system. In this work, three inputs that are affecting energy use of the chiller system are selected i.e. 1) refrigerant tonnage,...
Electricity is one of the most important needs of human life. In order to provide this need sufficiently, demand for the electricity needs to be predicted in advance. Conducting production oriented studies based on the estimation results is a must. In this study, electricity consumption data of Turkey between the years 1970 and 2014 were collected from Turkish Statistical Institute. Using these data,...
The Artificial Neural Network (ANN) is a branch of science in the field of artificial intelligence and is created from adapting the workings of the human brain. Backpropagation (BP) and Learning Vector Quantisation (LVQ) are two of many methods used to recognise patterns. Both are supervised training methods with different approaches. BP uses an error value to recognise patterns or images, while LVQ...
Brain-Computer Interface (BCI) can be realized by translating user's thoughts into control commands to assist paralyzed persons to communicate and control electronic devices. In this work, Electroencephalographic (EEG) signals were recorded from four subjects while they perform different mental states. We present an Artificial-Neural-Network-based approach for the purpose of classifying Electroencephalographic...
In present paper, authors develop a model for estimation of earth slope stability based on the artificial neural networks. For this purpose, authors engage multi-layer feed-forward network with Levenberg-Marquardt learning algorithm and 14 hidden nodes, using existing experimental data, and the results of traditional limit equilibrium analyzes of 57 different cases according to the predefined experimental...
Nowadays, as information systems are more open to the Internet, the importance of secure networks is tremendously increased. Interconnected systems such as web server data servers are now under the threats of network attackers. Intrusion Detection System (IDS) is the most powerful system that can handle the intrusions of the computer environments by triggering alerts to make the analysts take actions...
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