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Image colors are considerably affected by the intensity of the light source. In this paper, we propose a color constancy method using neural networks fusion to normalize images captured under sunlight with a variation of light intensities. A genetic algorithm is also applied to optimize the color normalization. A 24-patch Macbeth color checker is utilized as the reference to normalize the images....
Reducing power consumption has become a priority in microprocessor design as more devices become mobile and as the density and speed of components lead to power dissipation issues. Power allocation strategies for individual components within a chip are being researched to determine optimal configurations to balance power and performance. Modelling and estimation tools are necessary in order to understand...
This study examines the price estimation capability of MAIS (Multi-Agent Intelligent Simulator) when two types of agents with different learning capabilities coexist in a power trading market. This study identifies that the proposed MAIS, considering the coexistence of different types of agents, can improve its estimation accuracy of wholesale electricity price. This study also reexamines the estimation...
Estimating the amount of effort required for developing a software system is one of the most important project management concerns. This study successfully produces an optimal reduced linear model for software cost estimation by employing a series of methods of multiple regressions to identify the most significant explanatory variables of the fifteen COCOMO cost drivers. The results yielded by the...
Frequency is an important parameter in power system monitoring, control and protection. This paper shows how a combination of neural networks and genetic algorithm can be used to estimate power system frequency. Neural networks on the other hand offer great advantages in learning, adaptation, fault tolerance and parallelism. Genetic algorithm is a parallel global search technique that emulates natural...
Machine scheduling is a critical problem in industries where products are custom-designed. The wide range of products, the lack of previous experiences in manufacturing, and the several conflicting criteria used to evaluate the quality of the schedules define a huge search space. Furthermore, production complexity and human influence in each manufacturing step make time estimations difficult to obtain...
This paper suggested a novel method based on wavelet packet transform and radial basis function neural network (WPTRBFN) in simultaneous spectrophotometric determination of Mn (II), Zn (II), Co (II) and Cd (II) combining wavelet packet thresholding denoising with radial basis neural network. Wavelet packet representations of signals provided a local time–frequency description, thus in the wavelet...
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