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Urda, D., Subirats, J.L., Franco, L. and Jerez, J.M. (2010) Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles. IEA/AIE Springer-Verlag, Part I, LNAI 6096, 317-326.

has been cited by the following article:

• TITLE: Efficient VLSI Implementation of the C-MANTEC Conn Algorithm by Using PID Controllers

  AUTHORS: J. Jeya Caleb, M. Kannan

  KEYWORDS: C-MANTEC, PID, Generalization Capability, Cancer, Intelligent Control

  JOURNAL NAME: Circuits and Systems, Vol.8 No.11, November 3, 2017

  ABSTRACT: Through the research on the existing C-MANTEC neural network and PID control technology, this paper presents an improved C-MANTEC algorithm based on PID control system. The combining of the artificial neural networks with conventional PID control helps in exploring their respective advantages to forming the intelligent PID control. From UCI Repository cancer dataset, the developed system is tested. The results show that the scheme can not only improve the speed of the algorithm in the training process but also improve the generalization capability of the network, which further enhances the performance of PID controllers. The overall power consumed is also reduced to a greater extent.