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Empirical Determination And Forecastability Of Foreign Exchange Rate Of India., Rituparna Kar Dr. Dec 2009

Empirical Determination And Forecastability Of Foreign Exchange Rate Of India., Rituparna Kar Dr.

Doctoral Theses

The first chapter of this thesis begins with a brief review of the existing literature on foreign exchange rate models and their forecasting performance. Thereafter it presents the motivation as well as the main aspects of this study. The format of this chapter is as follows. A brief review of the relevant literature is presented in the first section. This review includes the important theoretical / structural as well as time series models of exchange rate. The motivation of the thesis is discussed in Section 1.2. Section 1.3 presents a brief account of the Indian economic reforms since 1993 with …

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Development Of A Web-Based Woody Biomass Energy Expert System, Sabina Dhungana May 2009

Development Of A Web-Based Woody Biomass Energy Expert System, Sabina Dhungana

Graduate Theses, Dissertations, and Problem Reports (ETD)

Woody biomass is evolving as a potential bioenergy feedstock at an industrial scale to provide the required supply for industries relying on these resources at necessary levels and feasible costs. In order to effectively utilize woody biomass for energy, it is essential to know in advance the availability of biomass, the equivalent energy provided, and the associated procurement costs. Expert systems, using computer based programming and containing knowledge bases reflecting the knowledge of human experts in the field, are being used in industrial facilities for real time problem analysis and knowledge enhancement. This study draws on this approach and attempts …

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Certain Pattern Recognition Tasks Using Genetic Programming., Durga Muni Dr. Apr 2009

Certain Pattern Recognition Tasks Using Genetic Programming., Durga Muni Dr.

Doctoral Theses

No abstract provided.

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Uncertainty Management Of Intelligent Feature Selection In Wireless Sensor Networks, Sanchita Mal-Sarkar Jan 2009

Uncertainty Management Of Intelligent Feature Selection In Wireless Sensor Networks, Sanchita Mal-Sarkar

ETD Archive

Wireless sensor networks (WSN) are envisioned to revolutionize the paradigm of monitoring complex real-world systems at a very high resolution. However, the deployment of a large number of unattended sensor nodes in hostile environments, frequent changes of environment dynamics, and severe resource constraints pose uncertainties and limit the potential use of WSN in complex real-world applications. Although uncertainty management in Artificial Intelligence (AI) is well developed and well investigated, its implications in wireless sensor environments are inadequately addressed. This dissertation addresses uncertainty management issues of spatio-temporal patterns generated from sensor data. It provides a framework for characterizing spatio-temporal pattern in …

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Intelligent Time-Successive Production Modeling, Yasaman Khazaeni Jan 2009

Intelligent Time-Successive Production Modeling, Yasaman Khazaeni

Graduate Theses, Dissertations, and Problem Reports (ETD)

A new framework is presented that uses production data history in order to build a field-wide performance prediction model. In this work artificial intelligence techniques and data driven modeling are utilized to perform a future production prediction for both synthetic and real field cases.;Production history is paired with geological information from the field to build large dataset containing the spatio-temporal dependencies amongst different wells. These spatio-temporal dependencies are addressed by information from Closest Offset Wells (COWs). This information includes geological characteristics (Spatial) and dynamic production data (Temporal) of all COWs.;Upon creation of the dataset, this framework calls for development of …

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Concept Learning By Example Decomposition, Sameer Joshi Jan 2009

Concept Learning By Example Decomposition, Sameer Joshi

Electronic Theses and Dissertations

For efficient understanding and prediction in natural systems, even in artificially closed ones, we usually need to consider a number of factors that may combine in simple or complex ways. Additionally, many modern scientific disciplines face increasingly large datasets from which to extract knowledge (for example, genomics). Thus to learn all but the most trivial regularities in the natural world, we rely on different ways of simplifying the learning problem. One simplifying technique that is highly pervasive in nature is to break down a large learning problem into smaller ones; to learn the smaller, more manageable problems; and then to …

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Development Of An Open Loop Fuzzy Logic Urea Dosage Controller For Use With An Scr Equipped Hdd Engine, Theodore R. Adams Dec 2008

Development Of An Open Loop Fuzzy Logic Urea Dosage Controller For Use With An Scr Equipped Hdd Engine, Theodore R. Adams

Graduate Theses, Dissertations, and Problem Reports (ETD)

Selective Catalytic Reduction (SCR) has been shown to be the most promising exhaust aftertreatment system for reducing oxides of nitrogen in near term in-use applications. SCRs use the ammonia containing compound urea, as a reducing agent. In order to control the urea dosage during transient operation of the engine, sophisticated control strategies are needed. The goal of this study was to design a controller to achieve the maximum NO x emission reduction possible in the transient mode of engine operation, without causing ammonia slip. The development of an open loop, non-sensor based fuzzy logic urea dosage controller is discussed in …

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Real-Time Automatic Price Prediction For Ebay Online Trading, Ilya Igorevitch Raykhel Nov 2008

Real-Time Automatic Price Prediction For Ebay Online Trading, Ilya Igorevitch Raykhel

Theses and Dissertations

While Machine Learning is one of the most popular research areas in Computer Science, there are still only a few deployed applications intended for use by the general public. We have developed an exemplary application that can be directly applied to eBay trading. Our system predicts how much an item would sell for on eBay based on that item's attributes. We ran our experiments on the eBay laptop category, with prior trades used as training data. The system implements a feature-weighted k-Nearest Neighbor algorithm, using genetic algorithms to determine feature weights. Our results demonstrate an average prediction error of 16%; …

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Pilot In Loop Assessment Of Fault Tolerant Flight Control Schemes In A Motion Flight Simulator, Girish Kumar Sagoo Aug 2008

Pilot In Loop Assessment Of Fault Tolerant Flight Control Schemes In A Motion Flight Simulator, Girish Kumar Sagoo

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research presents the pilot in the loop tests carried out in a Six-Degree of Freedom (6-DOF) motion flight simulator to evaluate failure detection, isolation and identification (FDII) schemes for an advanced F-15 aircraft. The objective behind this study is to leverage the capability of the flight simulator at West Virginia University (WVU) to carry out a performance assessment of neurally augmented control algorithms developed on a Matlab/Simulink RTM platform. The experimental setup features an interface setup of Gen-2 SimulinkRTM schemes with MOTUS Flight Simulator (MFS). The set up is a close substitute to a real flight and thus is …

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Pre And Postprocessing In Klass, Karina Gibert, R. Nonell Jul 2008

Pre And Postprocessing In Klass, Karina Gibert, R. Nonell

International Congress on Environmental Modelling and Software

KLASS (Gibert et alt 2005b) is a software originally conceived for Knowledge Discovery(KDD) in real domains with complex structure (Gibert et alt 1999). It provides some mixturesof statistical and artificial intelligence tools to support KDD, including basic statistics andproviding an integrated system to support the whole process of KDD including pre and postprocessing, provided that the main data mining technique to be used is related with clusteringor rule induction (Gibert et alt 2005c).

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On The Role Of Pre And Post-Processing In Environmental Data Mining, Karina Gibert, Joaquín Izquierdo, Geoffrey Holmes, Ioannis N. Athanasiadis, Joaquim Comas, Miquel Sànchez-Marrè Jul 2008

On The Role Of Pre And Post-Processing In Environmental Data Mining, Karina Gibert, Joaquín Izquierdo, Geoffrey Holmes, Ioannis N. Athanasiadis, Joaquim Comas, Miquel Sànchez-Marrè

International Congress on Environmental Modelling and Software

The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. …

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The Event Bush As A Potential Complex Methodology Of Conceptual Modelling In The Geosciences, C. A. Pshenichny, S. I. Nikolenko, R. Carniel, A. L. Sobissevitch, P. A. Vaganov, Z. V. Khrabrykh, V. P. Moukhachov, V. L. Shterkhun, A. A. Rezyapkin, A. V. Yakovlev, R. A. Fedukov, E. A. Gusev Jul 2008

The Event Bush As A Potential Complex Methodology Of Conceptual Modelling In The Geosciences, C. A. Pshenichny, S. I. Nikolenko, R. Carniel, A. L. Sobissevitch, P. A. Vaganov, Z. V. Khrabrykh, V. P. Moukhachov, V. L. Shterkhun, A. A. Rezyapkin, A. V. Yakovlev, R. A. Fedukov, E. A. Gusev

International Congress on Environmental Modelling and Software

The event bush is a new method of artificial intelligence proposed specially tomeet the needs of geosciences, from basic research to communication with nonprofessionals.First results of its application as well as combination of event bush withmathematical and logical formalisms are encouraging, and the method has shown someadvantages to existing approaches, as well as an ability to unite them and become acomplex integrated methodology. However, since the very first steps, it turned out that theway of thinking that underlies event bush differs from virtually all existing pathways ofthought perceived in the Earth sciences. This paper aims to provide the practical guidelinesfor …

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Simulation And Visualization Of Environments With Multidimensional Time, Luther A. Tychonievich Jan 2008

Simulation And Visualization Of Environments With Multidimensional Time, Luther A. Tychonievich

Theses and Dissertations

This work introduces the notion of computational hypertime, or the simulation and visualization of hypothetical environments possessing multidimensional time. An overview of hypertime is provided,including an intuitive visualization paradigm and a discussion of the failure of common simulation techniques when extended to include multidimensional time. A condition for differential equations describing hypertime motion to be amenable to standard time-iterative simulation techniques is provided,but is not satisfied by any known model of physics. An alternate simulation algorithm involving iterative refinement of entire equations of motion is presented,with an example implementation to solve elastic collisions in hypertime. An artificial intelligence algorithm for …

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Review On Technical Aspects Of Image Acquisition, Analysis And Retrieval For Leukaemia Cells, S. Rajendran, Hamzah Arof, Fatimah Ibrahim, S. Yegappan Jan 2008

Review On Technical Aspects Of Image Acquisition, Analysis And Retrieval For Leukaemia Cells, S. Rajendran, Hamzah Arof, Fatimah Ibrahim, S. Yegappan

Research Publications (2006 to 2010)

This paper reviews the technical aspects of the state-of-art techniques and procedures for image acquisition, pre-processing, image processing and analysis, search and retrieval techniques for leukaemia blood cell images. Hospital Ampang gets a fair amount of leukaemia cases every year but the hematology department of Hospital Ampang lacks the digital format of patient management system and leukaemia images storage and retrieval system. So, a survey on technical aspects of acquisition, analysis and retrieval was conducted to propose and develop patient management system and leukaemia diagnosis support system for Hospital Ampang, Malaysia. © 2008 Springer-Verlag.

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Learning Policies For Embodied Virtual Agents Through Demonstration, Jonathan Dinerstein, Parris K. Egbert, Dan A. Ventura Jan 2008

Learning Policies For Embodied Virtual Agents Through Demonstration, Jonathan Dinerstein, Parris K. Egbert, Dan A. Ventura

Faculty Publications

Although many powerful AI and machine learning techniques exist, it remains difficult to quickly create AI for embodied virtual agents that produces visually lifelike behavior. This is important for applications (e.g., games, simulators, interactive displays) where an agent must behave in a manner that appears human-like. We present a novel technique for learning reactive policies that mimic demonstrated human behavior. The user demonstrates the desired behavior by dictating the agent’s actions during an interactive animation. Later, when the agent is to behave autonomously, the recorded data is generalized to form a continuous state-to-action mapping. Combined with an appropriate animation algorithm …

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A Unified Framework For Solving Multiagent Task Assignment Problems, Kevin Cousin Dec 2007

A Unified Framework For Solving Multiagent Task Assignment Problems, Kevin Cousin

Theses and Dissertations

Multiagent task assignment problem descriptors do not fully represent the complex interactions in a multiagent domain, and algorithmic solutions vary widely depending on how the domain is represented. This issue is compounded as related research fields contain descriptors that similarly describe multiagent task assignment problems, including complex domain interactions, but generally do not provide the mechanisms needed to solve the multiagent aspect of task assignment. This research presents a unified approach to representing and solving the multiagent task assignment problem for complex problem domains. Ideas central to multiagent task allocation, project scheduling, constraint satisfaction, and coalition formation are combined to …

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Parallelization Of Ant Colony Optimization Via Area Of Expertise Learning, Adrian A. De Freitas Sep 2007

Parallelization Of Ant Colony Optimization Via Area Of Expertise Learning, Adrian A. De Freitas

Theses and Dissertations

Ant colony optimization algorithms have long been touted as providing an effective and efficient means of generating high quality solutions to NP-hard optimization problems. Unfortunately, while the structure of the algorithm is easy to parallelize, the nature and amount of communication required for parallel execution has meant that parallel implementations developed suffer from decreased solution quality, slower runtime performance, or both. This thesis explores a new strategy for ant colony parallelization that involves Area of Expertise (AOE) learning. The AOE concept is based on the idea that individual agents tend to gain knowledge of different areas of the search space …

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Scaling Ant Colony Optimization With Hierarchical Reinforcement Learning Partitioning, Erik J. Dries Sep 2007

Scaling Ant Colony Optimization With Hierarchical Reinforcement Learning Partitioning, Erik J. Dries

Theses and Dissertations

This research merges the hierarchical reinforcement learning (HRL) domain and the ant colony optimization (ACO) domain. The merger produces a HRL ACO algorithm capable of generating solutions for both domains. This research also provides two specific implementations of the new algorithm: the first a modification to Dietterich's MAXQ-Q HRL algorithm, the second a hierarchical ACO algorithm. These implementations generate faster results, with little to no significant change in the quality of solutions for the tested problem domains. The application of ACO to the MAXQ-Q algorithm replaces the reinforcement learning, Q-learning and SARSA, with the modified ant colony optimization method, Ant-Q. …

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A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09 Jan 2007

A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09

CGU Faculty Publications and Research

Consumer health information written by health care professionals is often inaccessible to the consumers it is written for. Traditional readability formulas examine syntactic features like sentence length and number of syllables, ignoring the target audience's grasp of the words themselves. The use of specialized vocabulary disrupts the understanding of patients with low reading skills, causing a decrease in comprehension. A naive Bayes classifier for three levels of increasing medical terminology specificity (consumer/patient, novice health learner, medical professional) was created with a lexicon generated from a representative medical corpus. Ninety-six percent accuracy in classification was attained. The classifier was then applied …

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Repurposing A Roomba: Evaluating And Training Behavior In A Simple Agent, Donald Samuel Abbott-Mccune Jan 2007

Repurposing A Roomba: Evaluating And Training Behavior In A Simple Agent, Donald Samuel Abbott-Mccune

Theses and Dissertations

Recent attempts to reprogram a Roomba to be used as a simple agent have led to interesting behavior. Observation has shown that the behavior of the Roomba is not only dependent on the precepts of the Roomba, but also relies heavily on the uncontrollable environmental conditions that the Roomba is placed in. Ultimately this makes the Roomba a great platform to test and teach aspects of artificial intelligence. This paper will show how most of the tested environmental conditions are mitigated by a learning agent that will adjust behavior dependent on the precepts that are received.

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Observational Intelligence: An Overview Of Computational Actual Entities And Their Use As Agents Of Artificial Intelligence, Brandon Scot Saunders Jan 2007

Observational Intelligence: An Overview Of Computational Actual Entities And Their Use As Agents Of Artificial Intelligence, Brandon Scot Saunders

Theses and Dissertations

This thesis' focus is on the use of Alfred North Whitehead's concept of Actual Entities as a computational tool for computer science and the introduction of a novel usage of Actual Entities as learning agents. Actual Entities are vector based agents that interact within their environment through a process called prehension. It is the combined effect of multiple Actual Entities working within a Colony of Prehending Entities that produces emergent, intelligent behavior. It is not always the case that prehension functions for desired behavior are known beforehand and frequently the functions are too complex to construct by hand. Through the …

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Improving The Prediction Of The Behaviour Of Masonry Wall Panels Using Model Updating And Artificial Intelligence Techniques, Chengfei Sui Jan 2007

Improving The Prediction Of The Behaviour Of Masonry Wall Panels Using Model Updating And Artificial Intelligence Techniques, Chengfei Sui

School of Engineering, Computing and Mathematics Theses

Out-of-plane laterally loaded masonry wall panels are still much used in modem structures. However due to their anisotropic and highly composite nature, it is extremely difficult to understand their behaviour and to date there is no analytical method that is capable of accurately predicting the response of masonry panels to the applied loadings. This is one of the major obstacles in analysing and designing masonry structures. This research studied a new method that accurately predicts the response of laterally loaded masonry wall panels. In this dissertation, the method of using corrector factors developed by previous researchers was further studied using …

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Using Machine Learning Techniques To Create Ai Controlled Players For Video Games, Bhuman Soni Jan 2007

Using Machine Learning Techniques To Create Ai Controlled Players For Video Games, Bhuman Soni

Theses : Honours

This study aims to achieve higher replay and entertainment value in a game through human-like AI behaviour in computer controlled characters called bats. In order to achieve that, an artificial intelligence system capable of learning from observation of human player play was developed. The artificial intelligence system makes use of machine learning capabilities to control the state change mechanism of the bot. The implemented system was tested by an audience of gamers and compared against bats controlled by static scripts. The data collected was focused on qualitative aspects of replay and entertainment value of the game and subjected to quantitative …

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Design And Simulation Of Advanced Fault Tolerant Flight Control Schemes, Srikanth Gururajan Jan 2006

Design And Simulation Of Advanced Fault Tolerant Flight Control Schemes, Srikanth Gururajan

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research effort describes the design and simulation of a distributed Neural Network (NN) based fault tolerant flight control scheme and the interface of the scheme within a simulation/visualization environment. The goal of the fault tolerant flight control scheme is to recover an aircraft from failures to its sensors or actuators. A commercially available simulation package, Aviator Visual Design Simulator (AVDS), was used for the purpose of simulation and visualization of the aircraft dynamics and the performance of the control schemes.;For the purpose of the sensor failure detection, identification and accommodation (SFDIA) task, it is assumed that the pitch, roll …

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Instantaneously Trained Neural Networks With Complex And Quaternion Inputs, Adityan V. Rishiyur Jan 2006

Instantaneously Trained Neural Networks With Complex And Quaternion Inputs, Adityan V. Rishiyur

LSU Master's Theses

Neural network architectures such as backpropagation networks, perceptrons or generalized Hopfield networks can handle complex inputs but they require a large amount of time and resources for the training process. This thesis investigates instantaneously trained feedforward neural networks that can handle complex and quaternion inputs. The performance of the basic algorithm has been analyzed and shown how it provides a plausible model of human perception and understanding of images. The motivation for studying quaternion inputs is their use in representing spatial rotations that find applications in computer graphics, robotics, global navigation, computer vision and the spatial orientation of instruments. The …

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Stability Monitoring And Analysis Of Online Learning Neural Networks, Sampath Yerramalla Dec 2005

Stability Monitoring And Analysis Of Online Learning Neural Networks, Sampath Yerramalla

Graduate Theses, Dissertations, and Problem Reports (ETD)

On-line adaptation using soft-computational learning methods is on the rise for use in safety-critical applications such as fault-tolerant flight control, maintenance of distributed networks, implementation of high security devices, etc. The inapplicability of traditional analysis methods is limiting the wider use of soft-computational learning methods in safety-critical applications that involve online adaptation. The focus of the research is the development of non-conventional analysis techniques for the testing, verification, validation and analysis of adaptive learning components such as the online learning neural networks.;Our research considers stability of online adaptation as a heuristic measure of correctness in the operation of the adaptive …

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Event-Driven Document Selection For Terrorism, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Teng-Kwee Ong, Rohan Kumar Gunaratna May 2005

Event-Driven Document Selection For Terrorism, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Teng-Kwee Ong, Rohan Kumar Gunaratna

Research Collection School Of Computing and Information Systems

In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these event related instances, one should ideally perform the task on the relevant documents only. We have therefore proposed some document selection strategies based on information extraction (IE) patterns. Each strategy attempts to select one document at a time such that the gain of event related instance information is maximized. Our …

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Salient Closed Boundary Extraction With Ratio Contour, Song Wang, Toshiro Kubota, Jeffrey Mark Siskind, Jun Wang Apr 2005

Salient Closed Boundary Extraction With Ratio Contour, Song Wang, Toshiro Kubota, Jeffrey Mark Siskind, Jun Wang

Faculty Publications

We present ratio contour, a novel graph-based method for extracting salient closed boundaries from noisy images. This method operates on a set of boundary fragments that are produced by edge detection. Boundary extraction identifies a subset of these fragments and connects them sequentially to form a closed boundary with the largest saliency. We encode the Gestalt laws of proximity and continuity in a novel boundary-saliency measure based on the relative gap length and average curvature when connecting fragments to form a closed boundary. This new measure attempts to remove a possible bias toward short boundaries. We present a polynomial-time algorithm …

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An Evolutionary Algorithm To Generate Ellipsoid Detectors For Negative Selection, Joseph M. Shapiro Mar 2005

An Evolutionary Algorithm To Generate Ellipsoid Detectors For Negative Selection, Joseph M. Shapiro

Theses and Dissertations

Negative selection is a process from the biological immune system that can be applied to two-class (self and nonself) classification problems. Negative selection uses only one class (self) for training, which results in detectors for the other class (nonself). This paradigm is especially useful for problems in which only one class is available for training, such as network intrusion detection. Previous work has investigated hyper-rectangles and hyper-spheres as geometric detectors. This work proposes ellipsoids as geometric detectors. First, the author establishes a mathematical model for ellipsoids. He develops an algorithm to generate ellipsoids by training on only one class of …

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Morphological Tower: A Tool For Multi-Scale Image Processing., Susanta Mukhopadhyay Dr. Feb 2005

Morphological Tower: A Tool For Multi-Scale Image Processing., Susanta Mukhopadhyay Dr.

Doctoral Theses

An image is a recorded replication of natural scene or objects using suitable sensor and recording media. The visual quality of the recorded image may be enhanced using various types of low-level processing namely noise smoothing, contrast enhancement. The images of the same scene recorded by several sensors reveal more inforination but in their own respective ways. This advantage of multi-sensor imaging system is real- ized through the fusion of the multimodal images. One more important higher-level processing is segmentation where the image is decomposed into a set of meaningful regions ( e.g. objects and background). An image, in general, …

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