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In a deregulated electricity market where consumers can prepare bidding plans and purchase electricity directly from supplies, consumers can expect the price to fluctuate based on the demand. The consumers can also make economic beneficial decision to use electricity when the price is low. In this context, accurate forecast of the electricity price enable the consumers to plan and make such decisions...
This paper presents the development of forecast models for a wind farm producibility with a 24 hours horizon. The aim is to obtain accurate wind power predictions by using feedforward artificial neural networks. In particular, different forecasting models are developed and for each of them the best architecture is researched by means of sensitivity analysis, modifying the main parameters of the artificial...
Plant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were pre-processed. After than each image was scanned by 5×5 overlapping filter and median values of each filter process were recorded to represent the leaves. After...
In this paper, a simple artificial neural network power system stabilizer (SANN-PSS) is implemented using a reduced order power system. Knowledge of the high bus voltage of a transformer is employed to alter the Heffron-Phillips' method. Furthermore, a reduction technique is applied to change the power system's sequence, and increase the power system's stability by adjusting the controller's parameters...
The main aim of recognising gestures is to build a system that can identify human gestures that are specific and then to use them to put forth desired information to the device. By using mathematical algorithms, human gestures can be interpreted. This is referred to as Gesture Recognition. Mudra is an expressive form of gesture that is mainly used in Indian classical dance form where the gesture is...
Nowadays Opinion mining is given more important, since it provides decision makers to estimate the success of a newly proposed techniques, novel ad campaign or novel product launch. In general, supervised methods such as Support Vector Machine (SVM) and Artificial Neural Network (ANN) are used to classify the opinions. In some cases SVM performs better classification and some cases ANN performs better...
The ability of the machine to infer knowledge from the user documents can be tested based on its ability to answer the question asked. Conventional Artificial Neural Network (ANN) models for knowledge extraction only answer to the questions which are simple and objective as they don't analyze the questions and don't try to understand what really the content of document mean. The proposed question...
Swarm operation in Unmanned Aerial Vehicles is an emerging technology which has numerous uses. It can be used in industrial, agricultural, and even military applications. However, it must be able to perform formations for it to be effective. Also, countermeasures must be made by the swarm to account for certain obstructions that are present in the environment. This paper aims to address this issue...
This paper describes the identification of a nonlinear time invariant system is quite essential for its stability point of view. Among all the identification approaches, FLANNs is the best one but in case of learning speed and convergence point of view it does not work well. Amongst all the traditional approaches, a newly developed algorithm named ELMs (Extreme Learning Machine) for identification...
This paper presents a new algorithm for colorizing gray scale natural still images. The algorithm uses artificial neural network (ANN) to predict the low frequency discrete cosine transform (DCT) components of the RGB channels. A set of natural color images are used to train three ANNs. The trained networks estimates the RGB layers of the gray scale image that best match a set of training colored...
This paper presents a new method in forecasting Philippine Peso to US Dollar exchange rate. Compared to the conventional way, in which the Philippine Dealing System (PDS), as monitored by the Central Bank, determines the rate by analysing demand and supply, the use of artificial neural network, having consumer price index, inflation rate, lending interest rate and purchasing power of the peso as the...
One of the significant factor of privacy is the source of sound. It creates the level that determines the effectiveness of the other factor. To experience maximum privacy, cancelling of unwanted sound is necessary. To automate the design of sound masking, this proposal use Genetic Algorithm and Artificial Neural Network (SMUGAAN). By evolutionary method two stages are use: a) to determine the target...
This research develops an automatic questionnaire survey model. In the proposed model, the questions in the questionnaires can be converted into structured components and the component characteristics can be obtained from the collective online message. By using the Artificial Neural Network method, the relationship model between the collective message and questionnaire questions can be derived and...
Today, breast cancer is one of the most frequently seen cancer types. Analyses of breast cells characteristics have great importance in diagnosis, treatment and following of this disease. In this study, classification of 699 instances of breast cancer data that is available in UCI is performed through two different types of artificial neural network algorithm. In the literature, numerous algorithms...
In this study, a classification application is realized to determine the deformation status of the cutting disc. 673 cutting experiments data obtained from a marble cutting machine suited in a laboratuvary of the Afyon Kocatepe University are evaluated for this purpose. During the cutting process, 8 different signals (Axial forces (Fx, Fy, Fz), Noise, Peripheral speed of the disc, Current, Voltage...
Separation of thyroid nodules which are often morphologically similar is a significant task. Due to this similarity, different pathologist may fail to correctly evaluate and misdiagnose the lesions. Such misdiagnoses lead to substantial problems such as late recovery and unnecessary treatment process and costs. Use of immunohistochemical dyes help pathologists correctly diagnose the cases where morphologically...
Incorporating knowledge from domain expert to a classifier is one of the techniques which require to be considered in solving imbalanced dataset problems. In this study, the proposed technique is a development to extend the process for imbalanced dataset where the individual classification system has already been designed for balanced data set. This paper introduces a methodology and preliminary results...
The feasibility of automating the evaluation of stroke chronic patients' motor functions has been explored while analyzing their corresponding fMRI studies with statistical parametric analysis, statistical inference analysis and a nonlinear multivoxel pattern-analysis classifier based on a feed-forward backward-propagation neural network. After doing principal component analysis and independent component...
This work proposes to use Radial Basis Function - RBF artificial neural network and Multi-Layer Perceptron MLP with the algorithm cross-validation leave-one-out, to reduce the false-positives of suspicious regions automatically detected by a difference-of-Gaussian filter in mammography. This method was applied to 175 mammograms (one real lesion/image), from the Digital Database for Screening Mammography...
Robot environment map is used for the path planning. Sonar Sensor measurement is converted to the probabilistic representation of the environment (occupancy grid). In this paper we used sonar sensor model to identify the different regions of the robot on the floor (cells). We used the grid mapping to describe the emptiness and occupancy and the unknown areas of the robot environment and the nearby...
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