Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

Controlled redistribution of vibrational population by few-cycle strong-field laser pulses

The use of strong-field (i.e. intensities in excess of 10(13) Wcm(-2)) few-cycle ultrafast (durations of 10 femtoseconds or less) laser pulses to create, manipulate and image vibrational wavepackets is investigated. Quasi-classical modelling of the initial superposition through tunnel ionization, wavepacket modification by nonadiabatically altering the nuclear environment via the transition dipole and the Stark effect, and measuring the control outcome by fragmenting the molecule is detailed. The influence of the laser intensity on strong-field ultrafast wavepacket control is discussed in detail: by modifying the distribution of laser intensities imaged, we show that focal conditions can be created that give preference to this three-pulse technique above processes induced by the pulses alone. An experimental demonstration is presented, and the nuclear dynamics inferred by the quasi-classical model discussed. Finally, we present the results of a systematic investigation of a dual-control pulse scheme, indicating that single vibrational states should be observable with high fidelity, and the populated state defined by varying the arrival time of the two control pulses. The relevance of such strong-field coherent control methods to the manipulation of electron localization and attosecond science is discussed.

Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.