Download Computational Intelligence in Data Mining - Volume 1: by Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, PDF

By Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, Durga Prasad Mohapatra

The contributed quantity goals to explicate and deal with the problems and demanding situations for the seamless integration of 2 middle disciplines of machine technology, i.e., computational intelligence and knowledge mining. information Mining goals on the computerized discovery of underlying non-trivial wisdom from datasets through making use of clever research ideas. The curiosity during this learn region has skilled a substantial development within the final years as a result of key elements: (a) wisdom hidden in companies’ databases could be exploited to enhance strategic and managerial decision-making; (b) the massive quantity of information controlled via organisations makes it most unlikely to hold out a handbook research. The ebook addresses various equipment and methods of integration for reinforcing the general target of information mining. The e-book is helping to disseminate the data approximately a few leading edge, lively learn instructions within the box of knowledge mining, laptop and computational intelligence, besides a few present matters and purposes of comparable topics.

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Additional info for Computational Intelligence in Data Mining - Volume 1: Proceedings of the International Conference on CIDM, 20-21 December 2014

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5 Best solution comparison exact results while the GA implementation is slightly worse off for the test case networks with higher number of nodes and intersections. In Fig. 6, the comparison for worst solutions is shown. Here the hybrid algorithm does slightly better than both ACO and GA. Also, both the figure show near-linear relation between Total-Wait-Time and network size, validating the viability of the model for bigger networks. Figure 7 shows the comparison of empirical probability for all the algorithms of falling in the trap of bad solutions over multiple runs, thus giving a sub-optimal solution.

Keywords Fuzzy multilayer perceptron Gravitational search Particle swarm optimization Breast cancer Heart disease Hepatitis Liver disorder Lung cancer Classification Medical data Á Á Á Á Á Á Á 1 Introduction In recent years, the incorporation of soft computing approaches in medical diagnosis has achieved a new tendency to be employed successfully in a large number of medical applications. Many of the medical diagnosis procedures can be grouped T. K. S. S. C. Jain et al. 1007/978-81-322-2205-7_4 35 36 T.

Laxmi horizontal beam known as main rotor and tail rotor which is driven by a DC motor and it is counter balanced by a pivoted beam [1]. The TRMS can rotate in both horizontal and vertical direction. The main rotor generates a lift force due to this the TRMS moves in upward direction around the pitch axis. While, due to the tail rotor TRMS moves around the yaw axis. However TRMS resembles with the helicopter but there is some significant differences between helicopter and TRMS. In helicopter, by changing the angle of attack controlling has been done, while in TRMS it has been done by changing the speed of rotors.

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