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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 introduce a novel design of the static VAR compensator (SVC) controller for damping power system oscillations. A multi layer neural network model tuned by Grey Wolf Optimization algorithm (GWO) is investigated and presented. GWO search algorithm is used to optimized all the connection of weights and biases for the artificial neural network. The proposed approach depends up on the expected...
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...
Signature analysis methods have been proven to deliver good results in the laboratory environment and successfully applied to isolated motors. The influence of fault signal on a non-faulty motor may be interpreted as faulty condition of the healthy motor. Therefore, it is difficult to identify a motor fault within a network and precisely identify the type of fault. This paper presents a supervised...
This paper presents a novel application of machine learning techniques to the automatic detection of building rooftops in satellite images. The image is first segmented into homogeneous regions using the k-means algorithm. These segments are then treated as candidate rooftop regions which are presented to a novel two-stage classification process, features are extracted from each segment and submitted...
This paper presents a new image encryption technique based on neural chaotic generator. This encryption technique includes two main operations, permutation at pixel level and masking and permutation at bit level. The chaotic generator used in the encryption of image is perturbed by a new technique done by artificial neural network. Simulations show that the proposed encryption technique is effective...
This research work presents a systematic investigational study of an interesting challenging phenomenon observed in natural world. Mainly, presented study concerned with conceptual interdisciplinary analysis and evaluation of quantified learning creativity phenomenon. Associated with diverse aspects of measurable behavioral learning performance. That's observed by two diverse natural biological systems'...
In this paper, the application of an Artificial Neural Network (ANN) for remedial action of a power system is presented. The aims of this study are to find the significant control action that alleviates a bus voltage violation of a power system and to demonstrate the ability of a neural network in terms of evaluating the generation re-dispatch and load shedding amounts. The remedial action is based...
Searching for the next hop node in mobile sparse wireless sensor networks for data exchange is a challenging task. This involves frequently sending radio beacons that drain battery power and reduces the life of the sensor node. This work proposes a novel energy efficient approach of adaptively sampling the network connectivity. The adaptive sampling starts with random sampling of the network to collect...
In traditional language identification methods, it is not so easy for search engines to find relevant language database of a given query. Therefore, there is a need to identify the relevant user’s natural language query of unknown document database in a better way by automatic language identification. This novel approach presents an automatic method for classification of English and Arabic language...
Artificial Neural Networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of a simple ANN topology for load forecasting model with much improved accuracy for the Regional Power Control Centre of Saudi Electricity Company. The proposed system is based on optimising the initial random...
This paper presents a novel ANN based technique for improving the performance of distance relays against open circuit faults in transmission networks. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open conductor condition in HVTL but also to locate the place of this fault regardless the value of the pre-fault current loading. Detailed...
With the advent of the Internet, search engines were developed for English language because English language was a lingua franca. Currently, most of popular search engines such as Google and Yahoo! are available in more than 50 languages. However, these search engines have received less attention in South Asian languages especially, Urdu language. In this paper, we propose a novel approach for feature...
The drastic increase of residential load consumption in recent years result in over loading feeder lines and transformers for the Iraqi northern area distribution system especially in the city of Mosul. Solution for this problem requires up to date research consumers load study to find the proper solution to stop excess overload in the transformers and the feeders. This paper include the regional...
In natural world, it is observed that some non-human biological systems show diverse learning aspects. This work presents an interesting comparative study between two naturally inspired learning systems. These are: swarm smarts intelligence for example Ant Colony System (ACS); and behavioural animal learning of Thorndike's cat. The first ACS model used for solving optimally, Traveling Salesman Problem...
This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation...
Long-term load forecasting has a vital role in generation, transmission and distribution network planning. Traditional studies for long-term load forecasting were based on regression method, which could not provide a true representation of power system behavior in a volatile electricity market. The purpose of this paper is to introduce two approaches based regression method and artificial neural network...
A fast and efficient method for computing optimal grasping and manipulation forces is presented based on a Quadratic Optimisation formulation for a hand robotics system, where computation has been based on using the non-linear factual model of contacts. Furthermore, in order to achieve grasping while in motion, the Hand Inverse Jacobian has to be intensively computed, consequently, we investigate...
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