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Articles 4471 - 4500 of 4776

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Go Niche Or Go Home: Influence Maximization In The Presence Of Strong Opponent, Long Foong Liow Jan 2012

Go Niche Or Go Home: Influence Maximization In The Presence Of Strong Opponent, Long Foong Liow

Dissertations and Theses Collection (Open Access)

In hotly contested product categories dominated by a few powerful firms, it is quite common for weaker or late entrants to focus only on particular segments of the whole market. The rationale for such strategy is intuitive: to avoid direct confrontation with heavy-weight firms, and to concentrate in segments where these weaker firms have comparative advantages. In marketing, this is what people called “go niche or go home”. The niche-building strategy may rely on “homophily”, which implies that consumers in a particular market segment might possess certain set of attributes that cause them to appreciate certain products better (in other …

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Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong Jan 2012

Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong

Research Collection School Of Computing and Information Systems

We apply combinatorial auction as a coordination mechanism to smooth demands placed on suppliers' limited production capacities, allowing several manufacturers to share common suppliers effectively. Products are bidders bidding for parts from suppliers, consuming their capacities in different time periods. The fourth party logistic (4PL) provider acts as the auctioneer to coordinate bids and perform price iterations. We leverage on the strong links between the Lagrangian relaxation method and combinatorial auction, where the Lagrange multipliers serve as the supply capacity reserve prices, to balance the demand and supply of capacities. To prevent cyclic behaviour and to increase convergence speed, we …

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A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo Jan 2012

A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo

Research Collection School Of Computing and Information Systems

Sentiment analysis is a new area in text analytics where it focuses on the analysis and understanding of the human emotions from the text patterns. This new form of analysis has been widely adopted in customer relationship management especially in the context of complaint management. However, sentiment analysis using Twitter data has remained extremely difficult to manage due to sampling biasness. In this paper, we will discuss about the application of reweighting techniques in conjunction with online sentiment divisions to predict the vote percentage that individual presidential candidate in Singapore will receive in the Presidential Election 2011. There will be …

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Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao Jan 2012

Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao

Research Collection School Of Computing and Information Systems

Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our …

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Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau Jan 2012

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

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A Pomdp Model For Guiding Taxi Cruising In A Congested Urban City, Lucas Agussurja, Hoong Chuin Lau Nov 2011

A Pomdp Model For Guiding Taxi Cruising In A Congested Urban City, Lucas Agussurja, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We consider a partially observable Markov decision process (POMDP) model for improving a taxi agent cruising decision in a congested urban city. Using real-world data provided by a large taxi company in Singapore as a guide, we derive the state transition function of the POMDP. Specifically, we model the cruising behavior of the drivers as continuous-time Markov chains. We then apply dynamic programming algorithm for finding the optimal policy of the driver agent. Using a simulation, we show that this policy is significantly better than a greedy policy in congested road network.

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Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee Oct 2011

Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee

Research Collection School Of Computing and Information Systems

In this paper, we consider the problem of allocating machine resources among multiple agents, each of which is responsible to solve a flowshop scheduling problem. We present an iterated combinatorial auction mechanism in which bid generation is performed within each agent, while a price adjustment procedure is performed by a centralized auctioneer. While this approach is fairly well-studied in the literature, our primary innovation is in an adaptive price adjustment procedure, utilizing variable step-size inspired by adaptive PID-control theory coupled with utility pricing inspired by classical microeconomics. We compare with the conventional price adjustment scheme proposed in Fisher (1985), and …

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Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, Shih-Fen Cheng, Thi Duong Nguyen Aug 2011

Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, Shih-Fen Cheng, Thi Duong Nguyen

Research Collection School Of Computing and Information Systems

Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi fleet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are self-interested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform …

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A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal, Sarah M. Asio Jul 2011

A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal, Sarah M. Asio

Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research

The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To …

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Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau Jul 2011

Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We propose and explore, in the context of benchmark problems for flowshop scheduling, a risk-based concept of robustness for optimization problems. This risk-based concept is in distinction to, and complements, the uncertainty-based concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.

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Message-Passing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein Jul 2011

Message-Passing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Computing maximum a posteriori (MAP) estimation in graphical models is an important inference problem with many applications. We present message-passing algorithms for quadratic programming (QP) formulations of MAP estimation for pairwise Markov random fields. In particular, we use the concave-convex procedure (CCCP) to obtain a locally optimal algorithm for the non-convex QP formulation. A similar technique is used to derive a globally convergent algorithm for the convex QP relaxation of MAP. We also show that a recently developed expectation-maximization (EM) algorithm for the QP formulation of MAP can be derived from the CCCP perspective. Experiments on synthetic and real-world problems …

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Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint Jul 2011

Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

Research Collection School Of Computing and Information Systems

Multiagent planning has seen much progress with the development of formal models such as Dec-POMDPs. However, the complexity of these models -- NEXP-Complete even for two agents -- has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the Expectation-Maximization framework for likelihood maximization, we show that the necessary inference can be decomposed into processes that often involve a small subset of agents, thereby facilitating scalability. We …

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Real-World Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong Jul 2011

Real-World Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong

Research Collection School Of Computing and Information Systems

In this paper, we explore the idea of improving the efficiency of factorial design for parameter tuning of metaheuristics. In a standard full factorial design, the number of runs increases exponentially as the number of parameters. To reduce the parameter search space, one option is to first partition parameters into disjoint categories. While this may be done manually based on user guidance, an automated approach proposed in this paper is to apply a fractional factorial design to partition parameters based on their main effects where each partition is then tuned independently. With a careful choice of fractional design, our approach …

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Wolf Ant, Gilbert L. Peterson, Christopher M. Mayer, Kevin Cousin Jun 2011

Wolf Ant, Gilbert L. Peterson, Christopher M. Mayer, Kevin Cousin

Faculty Publications

Ant colony optimization (ACO) algorithms can generate quality solutions to combinatorial optimization problems. However, like many stochastic algorithms, the quality of solutions worsen as problem sizes grow. In an effort to increase performance, we added the variable step size off-policy hill-climbing algorithm called PDWoLF (Policy Dynamics Win or Learn Fast) to several ant colony algorithms: Ant System, Ant Colony System, Elitist-Ant System, Rank-based Ant System, and Max-Min Ant System. Easily integrated into each ACO algorithm, the PDWoLF component maintains a set of policies separate from the ant colony's pheromone. Similar to pheromone but with different update rules, the PDWoLF policies …

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Online Fault Detection Of Induction Motors Using Frequency Domain Independent Components Analysis, Zhaoxia Wang, C. S. Chang Jun 2011

Online Fault Detection Of Induction Motors Using Frequency Domain Independent Components Analysis, Zhaoxia Wang, C. S. Chang

Research Collection School Of Computing and Information Systems

This paper proposes an online fault detection method for induction motors using frequency-domain independent component analysis. Frequency-domain results, which are obtained by applying Fast Fourier Transform (FFT) to measured stator current time-domain waveforms, are analyzed with the aim of extracting frequency signatures of healthy and faulty motors with broken rotor-bar or bearing problem. Independent components analysis (ICA) is applied for such an aim to the FFT results. The obtained independent components as well as the FFT results are then used to obtain the combined fault signatures. The proposed method overcomes problems occurring in many existing FFT-based methods. Results using laboratory-collected …

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Supervisory Evolutionary Optimization Strategy For Adaptive Maintenance Schedules, Zhaoxia Wang, C. S. Chang Jun 2011

Supervisory Evolutionary Optimization Strategy For Adaptive Maintenance Schedules, Zhaoxia Wang, C. S. Chang

Research Collection School Of Computing and Information Systems

No abstract provided.

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A Feature Based Frequency Domain Analysis Algorithm For Fault Detection Of Induction Motors, Zhaoxia Wang, C. S. Chang, Zhang Yifan Jun 2011

A Feature Based Frequency Domain Analysis Algorithm For Fault Detection Of Induction Motors, Zhaoxia Wang, C. S. Chang, Zhang Yifan

Research Collection School Of Computing and Information Systems

This paper studies the stator currents collected from several inverter-fed laboratory induction motors and proposes a new feature based frequency domain analysis method for performing the detection of induction motor faults, such as the broken rotor-bar or bearing fault. The mathematical formulation is presented to calculate the features, which are called FFT-ICA features in this paper. The obtained FFT-ICA features are normalized by using healthy motor as benchmarks to establish a feature database for fault detection. Compare with conventional frequency-domain analysis method, no prior knowledge of the motor parameters or other measurements are required for calculating features. Only one phase …

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Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna Velagapudi, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri May 2011

Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna Velagapudi, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri

Research Collection School Of Computing and Information Systems

The use of distributed POMDPs for cooperative teams has been severely limited by the incredibly large joint policy- space that results from combining the policy-spaces of the individual agents. However, much of the computational cost of exploring the entire joint policy space can be avoided by observing that in many domains important interactions between agents occur in a relatively small set of scenarios, previously defined as coordination locales (CLs) [11]. Moreover, even when numerous interactions might occur, given a set of individual policies there are relatively few actual interactions. Exploiting this observation and building on an existing model shaping algorithm, …

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Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig May 2011

Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig

Research Collection School Of Computing and Information Systems

Distributed constraint optimization problems (DCOPs) are well-suited for modeling multi-agent coordination problems. However, most research has focused on developing algorithms for solving static DCOPs. In this paper, we model dynamic DCOPs as sequences of (static) DCOPs with changes from one DCOP to the next one in the sequence. We introduce the ReuseBounds procedure, which can be used by any-space ADOPT and any-space BnB-ADOPT to find cost-minimal solutions for all DCOPs in the sequence faster than by solving each DCOP individually. This procedure allows those agents that are guaranteed to remain unaffected by a change to reuse their lower and upper …

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Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy Varakantham, Shih-Fen Cheng, Thi Duong Nguyen May 2011

Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy Varakantham, Shih-Fen Cheng, Thi Duong Nguyen

Research Collection School Of Computing and Information Systems

This research is motivated by problems in urban transportation and labor mobility, where the agent flow is dynamic, non-deterministic and on a large scale. In such domains, even though the individual agents do not have an identity of their own and do not explicitly impact other agents, they have implicit interactions with other agents. While there has been much research in handling such implicit effects, it has primarily assumed controlled movements of agents in static environments. We address the issue of decision support for individual agents having involuntary movements in dynamic environments . For instance, in a taxi fleet serving …

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Message-Passing Algorithms For Large Structured Decentralized Pomdps, Akshat Kumar, Shlomo Zilberstein May 2011

Message-Passing Algorithms For Large Structured Decentralized Pomdps, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDPs provide a rigorous framework for multi-agent decision-theoretic planning. However, their high complexity has limited scalability. In this work, we present a promising new class of algorithms based on probabilistic inference for infinite-horizon ND-POMDPs---a restricted Dec-POMDP model. We first transform the policy optimization problem to that of likelihood maximization in a mixture of dynamic Bayes nets (DBNs). We then develop the Expectation-Maximization (EM) algorithm for maximizing the likelihood in this representation. The EM algorithm for ND-POMDPs lends itself naturally to a simple message-passing paradigm guided by the agent interaction graph. It is thus highly scalable w.r.t. the number of …

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Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato May 2011

Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato

Research Collection School Of Computing and Information Systems

In today's world, organizations are faced with increasingly large and complex problems that require decision-making under uncertainty. Current methods for optimizing such decisions fall short of handling the problem scale and time constraints. We argue that this is due to existing methods not exploiting the inherent structure of the organizations which solve these problems. We propose a new model called the OrgPOMDP (Organizational POMDP), which is based on the partially observable Markov decision process (POMDP). This new model combines two powerful representations for modeling large scale problems: hierarchical modeling and factored representations. In this paper we make three key contributions: …

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Random Keys Genetic Algorithms Scheduling And Rescheduling Systems For Common Production Systems, Elkin Rodriguez-Velasquez Apr 2011

Random Keys Genetic Algorithms Scheduling And Rescheduling Systems For Common Production Systems, Elkin Rodriguez-Velasquez

Engineering Management & Systems Engineering Theses & Dissertations

The majority of scheduling research deals with problems in specific production environments with specific objective functions. However, in many cases, more than one problem type and/or objective function exists, resulting in the need for a more generic and flexible system to generate schedules. Furthermore, most of the published scheduling research focuses on creating an optimal or near optimal initial schedule during the planning phase. However, after production processes start, circumstances like machine breakdowns, urgent jobs, and other unplanned events may render the schedule suboptimal, obsolete or even infeasible resulting in a "rescheduling" problem, which is typically also addressed for a …

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Measuring The Utility Of A Cyber Incident Mission Impact Assessment (Cimia) Process For Mission Assurance, Christy L. Peterson Mar 2011

Measuring The Utility Of A Cyber Incident Mission Impact Assessment (Cimia) Process For Mission Assurance, Christy L. Peterson

Theses and Dissertations

Information is a critical asset on which virtually all modern organizations depend upon to meet their operational mission objectives. Military organizations, in particular, have embedded Information and Communications Technologies (ICT) into their core mission processes as a means to increase their operational efficiency, exploit automation, improve decision quality, and shorten the kill chain. However, the extreme dependence upon ICT results in an environment where a cyber incident can result in severe mission degradation, or possibly failure, with catastrophic consequences to life, limb, and property. These consequences can be minimized by maintaining real-time situational awareness of mission critical resources so appropriate …

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Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo Jan 2011

Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo

Research Collection School Of Computing and Information Systems

This paper is concerned with automated tuning of parameters in local-search based meta-heuristics. Several generic approaches have been introduced in the literature that returns a ”one-size-fits-all” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instance-based automated tuning, but they are usually problem-specific. In this paper, we propose CluPaTra, a generic (problem-independent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as …

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Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu Jan 2011

Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu

Research Collection School Of Computing and Information Systems

This paper is concerned with the problem of Just-In-Time (JIT) job scheduling in a dynamic environment under uncertainty to attain timely service. We provide an approach, based on robust scheduling concepts, to analytically evaluate the expected cost of earliness and tardiness for each job and also the project. In addition, we search for a schedule execution policy with the minimum robust cost such that for a given risk level (epsilon), the actual realized schedule has (1 - epsilon) probability of completing with less than or equal to this robust cost. Our method is quite generic, and can be applied to …

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Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati Jan 2011

Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati

Research Collection School Of Computing and Information Systems

Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …

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Map Estimation For Graphical Models By Likelihood Maximization, Akshat Kumar, Shlomo Zilberstein Dec 2010

Map Estimation For Graphical Models By Likelihood Maximization, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Computing a maximum a posteriori (MAP) assignment in graphical models is a crucial inference problem for many practical applications. Several provably convergent approaches have been successfully developed using linear programming (LP) relaxation of the MAP problem. We present an alternative approach, which transforms the MAP problem into that of inference in a finite mixture of simple Bayes nets. We then derive the Expectation Maximization (EM) algorithm for this mixture that also monotonically increases a lower bound on the MAP assignment until convergence. The update equations for the EM algorithm are remarkably simple, both conceptually and computationally, and can be implemented …

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A Structure First Image Inpainting Approach Based On Self-Organizing Map (Som), Bo Chen, Zhaoxia Wang, Ming Bai, Quan Wang, Zhen Sun Dec 2010

A Structure First Image Inpainting Approach Based On Self-Organizing Map (Som), Bo Chen, Zhaoxia Wang, Ming Bai, Quan Wang, Zhen Sun

Research Collection School Of Computing and Information Systems

This paper presents a structure first image inpainting method based on self-organizing map (SOM). SOM is employed to find the useful structure information of the damaged image. The useful structure information which includes relevant edges of the image is used to simulate the structure information of the lost or damaged area in the image. The structure information is described by distinct or indistinct curves in an image in this paper. The obtained target curves separate the damaged area of the image into several parts. As soon as each part of the damaged image is restored respectively, the damaged image is …

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Automobile Exhaust Gas Detection Based On Fuzzy Temperature Compensation System, Zhiyong Wang, Hao Ding, Fufei Hao, Zhaoxia Wang, Zhen Sun, Shujin Li Dec 2010

Automobile Exhaust Gas Detection Based On Fuzzy Temperature Compensation System, Zhiyong Wang, Hao Ding, Fufei Hao, Zhaoxia Wang, Zhen Sun, Shujin Li

Research Collection School Of Computing and Information Systems

A temperature compensation scheme of detecting automobile exhaust gas based on fuzzy logic inference is presented in this paper. The principles of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer are discussed. A fuzzy inference system is designed to improve the measurement accuracy of the measurement equipment by reducing the measurement errors caused by environmental temperature. The case studies demonstrate the effectiveness of the proposed method. The fuzzy compensation scheme is promising as demonstrated by the simulation results in this paper.

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