Accurate Parameter Estimation of Contaminant Transport Inverse Problem using Paartaicle Swarm Optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

Benchmark Control Problem for Highway Bridge based on FLC

Fuzzy logic control (FLC) systems have been applied as an effective control system in various fields, including vibration control of structures. The advantage of this approach is its inherent robustness and ability to handle non‐linearities and uncertainties in structural behavior and loading. The study evaluates the three‐dimensional benchmark control problem for a seismically excited highway bridge using an ANFIS driven hydraulic actuators. An ANN based training strategy that considers both velocity and acceleration feedback together with a fuzzy logic rule base is developed. Present study needs only 4 accelerometers and 4 fuzzy rule bases to determine the control force, instead of 8 accelerometers and 4 displacement transducers used in the benchmark study problem. The results obtained are better than that obtained from the benchmark control algorithm.

Pickup and delivery problem using metaheuristics techniques

Dial-a-ride problem (DARP) is an optimization problem which deals with the minimization of the cost of the provided service where the customers are provided a door-to-door service based on their requests. This optimization model presented in earlier studies, is considered in this study. Due to the non-linear nature of the objective function the traditional optimization methods are plagued with the problem of converging to a local minima. To overcome this pitfall we use metaheuristics namely Simulated Annealing (SA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Immune System (AIS). From the results obtained, we conclude that Artificial Immune System method effectively tackles this optimization problem by providing us with optimal solutions. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.

The pursuit-evasion problem of two aircraft in a horizontal plane

The pursuit-evasion problem of two aircraft in a horizontal plane is modelled as a zerosum differential game with capture time as payoff. The aircraft are modelled as point masses with thrust and bank angle controls. The games of kind and degree for this differential game are solved.

Approach to the problem of ferroresonance in e.h.v. systems

An analytical analysis of ferroresonance with possible cases of its occurrence in series-and shunt-compensated systems is presented. A term `percentage unstable zoneÿ is defined to compare the jump severity of different nonlinearities. A direct analytical method has been shown to yield complete information. An attempt has been made to find all four critical points: jump-from and jump-to points of ferroresonance jump phenomena. The systems considered for analysis are typical 500 kV transmission systems of various lengths.

Relaxation: Application to the matrix reconstruction problem

This report describes some preliminary experiments on the use of the relaxation technique for the reconstruction of the elements of a matrix given their various directional sums (or projections).

Experimental implementation of quantumUlam’s problem in a nuclear magnetic resonance quantum information processor

The Ulam’s problem is a two person game in which one of the player tries to search, in minimum queries, a number thought by the other player. Classically the problem scales polynomially with the size of the number. The quantum version of the Ulam’s problem has a query complexity that is independent of the dimension of the search space. The experimental implementation of the quantum Ulam’s problem in a Nuclear Magnetic Resonance Information Processor with 3 quantum bits is reported here.

An extension of Mangler transformation to a 3-D problem

Considering the linearized boundary layer equations for three-dimensional disturbances, a Mangler type transformation is used to reduce this case to an equivalent two-dimensional one.

An inverse problem for Helmholtz equation

This article is concerned with subsurface material identification for the 2-D Helmholtz equation. The algorithm is iterative in nature. It assumes an initial guess for the unknown function and obtains corrections to the guessed value. It linearizes the otherwise nonlinear problem around the background field. The background field is the field variable generated using the guessed value of the unknown function at each iteration. Numerical results indicate that the algorithm can recover a close estimate of the unknown function based on the measurements collected at the boundary.