By M. Khoshnevisan, S. Bhattacharya, F. Smarandache
The aim of this e-book is to use the substitute Intelligence and keep an eye on platforms to diversified actual types. it's been designed for graduate scholars and researchers who're lively within the purposes of synthetic Intelligence and keep an eye on structures in modeling. In our destiny examine, we'll deal with the original features of Neutrosophic common sense in modeling and information research.
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Extra info for Artificial Intelligence and Responsive Optimization
The investor seems to display riskaverseness only when the market is equally likely to move in either direction and has a relatively high prior probability of staying unmoved. We have further outlined a suggested computational methodology to apply neutrosophic reasoning to the problem of 48 portfolio insurance. However, we leave the actual computational modeling of investor utility on a neutrosophic event space to a subsequent research endeavor. The door is now open for further research along these lines going deep into the governing utility structures that may underlie more complex derivative trading strategies, portfolio insurance schemes and structured financial products.
There is no reason why the highly intricate intracellular biochemical processes, which are inherently of a much higher order of complexity in terms of molecular kinetics compared to the BZ reaction, could not be better viewed in this light. In fact, experimental studies investigating the physiological clock (of yeast) due to oscillating enzymatic breakdown of sugar, have revealed that the coupling to membrane transport could, under certain conditions, result in chaotic biorhythms. The yeast does provide a useful experimental model for histologists studying cancerous cell growth because the ATM gene, believed to be a critical checkpoint in the S stage of the cell cycle, is related to the MEC1 yeast gene.
The yeast does provide a useful experimental model for histologists studying cancerous cell growth because the ATM gene, believed to be a critical checkpoint in the S stage of the cell cycle, is related to the MEC1 yeast gene. Zaguskin has further conjectured that all biorhythms have a discrete fractal structure. The almost ubiquitous growth function used to model population dynamics has the following well-known difference equation form: Xt+1 = rXt (1 – Xt/k) … (iv) Such models exhibit period-doubling and subsequently chaotic behavior for certain critical parameter values of r and k.
Artificial Intelligence and Responsive Optimization by M. Khoshnevisan, S. Bhattacharya, F. Smarandache