Engineering Commons^™

Grating Lobe Reduction In Aperiodic Linear Arrays Of Physically Large Antennas, William C. Barott, Paul G. Steffes

Publications

We present performance bounds obtained from the optimization of the sidelobe levels of aperiodic linear arrays. The antennas comprising these arrays are large compared to the distance between neighboring antennas, a case not addressed in previously published work. This optimization is performed in pattern-space and is applicable over a wide range of scan angles. We show that grating lobes can be suppressed even when the elemental antennas are several wavelengths in size, provided that the ratio of the antenna size to the average spacing between the antenna center-points does not exceed 80%.

An Investigation On The Use And Flexibility Of Genetic Algorithms For Logistic Regression, Sara Yoder

All Dissertations

Social scientists and other users of large data sets often desire a model to predict the probability that some condition exists, such as the probability that a person has diabetes or that a credit card transaction will be fraudulent. In general, this can be done by data mining techniques, which allow multiple records of data composed of numerous independent variables and one dependent variable to be examined in a statistical fashion to make a predictive model. One particular technique used is logistic regression. Logistic regression forms a predictive model based on a set of independent variables by assigning coefficients to …

A Genetic Approach To Voltage Collapse Mitigation, Dwarakesh Nallan Chakravartula

All Theses

The objective of this thesis is to provide an efficient and accurate corrective solution to a system that is on verge of voltage collapse. This thesis describes, in detail, the development of an optimization scheme that aims to alleviate power system instability and voltage collapse condition based on the principles of an evolutionary approach called Genetic Algorithm. The state of a system is determined using a voltage stability identifier termed Collapse Proximity Index (CPI) and the critical loading condition is identified. Applying principles of Genetic Algorithm, the critical system is brought back to a stable operating region. The sequential procedure …

Parameter Identification Of Hydro Generation System With Fluid Transients Based On Improved Genetic Algorithm, Lin Gao

Lin Gao

More accurate models are adopted for dynamic stability analysis of hydro generation systems but the parameters of these models are often estimated roughly. Inaccurate parameters may decrease the analysis accuracy improved by using an accurate model. An improved genetic algorithm is proposed in this paper to estimate the parameters of a hydro generation system model which contains a series of basic differential equations to represent the flow transients more accurately. The numerical and experimental results show good accordance between the actual systems and the identification results.

Rna Gene Finding With Biased Mutation Operators, Jennifer A. Smith

Jennifer A. Smith

The use of genetic algorithms for non-coding RNA gene finding has previously been investigated and found to be a potentially viable method for accelerating covariance-model-based database search relative to full dynamic-programming methods. The mutation operators in previous work chose new alignment insertion and deletion locations uniformly over the length of the model consensus sequence. Since the covariance models are estimated from multiple known members of a non-coding RNA family, information is available as to the likelihood of insertions or deletions at the individual model positions. This information is implicit in the state-transition parameters of the estimated covariance models. In the …

Searching For Protein Classification Features, Jennifer A. Smith

Jennifer A. Smith

A genetic algorithm is used to search for a set of classification features for a protein superfamily which is as unique as possible to the superfamily. These features may then be used for very fast classification of a query sequence into a protein superfamily. The features are based on windows onto modified consensus sequences of multiple aligned members of a training set for the protein superfamily. The efficacy of the method is demonstrated using receiver operating characteristic (ROC) values and the performance of resulting algorithm is compared with other database search algorithms.

A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith

Jennifer A. Smith

A genetic algorithm is proposed as an alternative to the traditional linear programming method for scoring covariance models in non-coding RNA (ncRNA) gene searches. The standard method is guaranteed to find the best score, but it is too slow for general use. The observation that most of the search space investigated by the linear programming method does not even remotely resemble any observed sequence in real sequence data can be used to motivate the use of genetic algorithms (GAs) to quickly reject regions of the search space. A search space with many local minima makes gradient decent an unattractive alternative. …

Bit-Error-Rate-Minimizing Channel Shortening Using Post-Feq Diversity Combining And A Genetic Algorithm, Gokhan Altin

Theses and Dissertations

In advanced wireline or wireless communication systems, i.e., DSL, IEEE 802.11a/g, HIPERLAN/2, etc., a cyclic prefix which is proportional to the channel impulse response is needed to append a multicarrier modulation (MCM) frame for operating the MCM accurately. This prefix is used to combat inter symbol interference (ISI). In some cases, the channel impulse response can be longer than the cyclic prefix (CP). One of the most useful techniques to mitigate this problem is reuse of a Channel Shortening Equalizer (CSE) as a linear preprocessor before the MCM receiver in order to shorten the effective channel length. Channel shortening filter …

Biogeography-Based Optimization: Synergies With Evolutionary Strategies, Immigration Refusal, And Kalman Filters, Dawei Du

ETD Archive

Biogeography-based optimization (BBO) is a recently developed heuristic algorithm which has shown impressive performance on many well known benchmarks. The aim of this thesis is to modify BBO in different ways. First, in order to improve BBO, this thesis incorporates distinctive techniques from other successful heuristic algorithms into BBO. The techniques from evolutionary strategy (ES) are used for BBO modification. Second, the traveling salesman problem (TSP) is a widely used benchmark in heuristic algorithms, and it is considered as a standard benchmark in heuristic computations. Therefore the main task in this part of the thesis is to modify BBO to …

Identification Of Human Gait Using Genetic Algorithm Tuned Fuzzy Logic, Abdallah Abdel-Rahman Hassan Mahmoud

Open Access Theses & Dissertations

Data mining is concerned with the discovery of useful hidden information in large databases. Classification is a data mining task producing rules in which a set of attributes in data predict the value of a class attribute. Classifiers usually produce a large number of rules, most of which are not interesting to the user. Rule interestingness is a decisive factor. However, evaluating rule interestingness is challenging as it involves both objective (data-driven) and subjective (user-driven) aspects.

In this research, a fuzzy genetic algorithm is proposed to discover classification rules that are both accurate and interesting. Continuous attributes are fuzzified so …

Singular Superposition/Boundary Element Method For Reconstruction Of Multi-Dimensional Heat Flux Distributions With Application To Film Cooling Holes, Mahmood Silieti, Eduardo Divo, Alain J. Kassab

Publications

A hybrid singularity superposition/boundary element-based inverse problem method for the reconstruction of multi-dimensional heat flux distributions is developed. Cauchy conditions are imposed at exposed surfaces that are readily reached for measurements while convective boundary conditions are unknown at surfaces that are not amenable to measurements such as the walls of the cooling holes. The purpose of the inverse analysis is to determine the heat flux distribution along cooling hole surfaces. This is accomplished in an iterative process by distributing a set of singularities (sinks) inside the physical boundaries of the cooling hole (usually along cooling hole centerline) with a given …

Constraint Handling Using Tournament Selection: Abductive Inference In Partly Deterministic Bayesian Network, Severino F. Galan, Ole J. Mengshoel

Ole J Mengshoel

Constraints occur in many application areas of interest to evolutionary computation. The area considered here is Bayesian networks (BNs), which is a probability-based method for representing and reasoning with uncertain knowledge. This work deals with constraints in BNs and investigates how tournament selection can be adapted to better process such constraints in the context of abductive inference. Abductive inference in BNs consists of finding the most probable explanation given some evidence. Since exact abductive inference is NP-hard, several approximate approaches to this inference task have been developed. One of them applies evolutionary techniques in order to find optimal or close-to-optimal …