Advances in Intelligent Systems Research

The link between stock returns and economic growth has been an important research topic in the financial economic literature. The purpose of this study is to employ a threshold vector autoregressive (TVAR) approach in order to investigate the non-linear relationship between stock returns and output growth...

In multimedia cellular network, a Mobile Host (MH) requests multimedia services and may experience handoffs to several cells. When the target cell cannot provide adequate bandwidth for a service, instead of directly dropping a request, the MH is put into the handoff queue and hopefully the request bandwidth...

In this paper, we present a new method for ranking generalized fuzzy numbers for dealing with fuzzy risk analysis problems. The proposed method considers the defuzzified values, the heights and the spreads of generalized fuzzy numbers, simultaneously, for ranking generalized fuzzy numbers. It gets better...

In this paper, we present two new methods for evaluating students’ answerscripts using vague values, where the evaluating marks awarded to the questions in the students’ answerscripts are represented by vague values. The vague mark awarded to each question of a student’s answerscript can be regarded...

OCR makes it possible for the user to edit or search the document’s contents. In this paper we describe a special water fill technique for detecting the upside down text document. Each character has a upside and downside filling capacities. A character may have two sides or one side filling capacity...

This paper presents a technique to improve the performance of laser phase-shift range finders. The phase measurement is performed by using a new method to extract the phase-shift data from the peak of received and transmitted intermediate frequency signal amplitudes. The pulse width modulation is used...

In this paper, accuracy improvement in the displacement measurement systems using Doppler-interferometry method is presented. The cross-talk error reduction methods are also discussed. Based on the mentioned method, a new nano-displacement measurement system is designed. In the designed system, the signal...

In this paper, design and simulation of a nanometric displacement measurement system is discussed. The combination of the Doppler effect and interferometry method is being used. A stabilized three-longitudinal-mode He-Ne laser with 632.8nm wavelength and 35cm cavity length is used. Its primary and secondary...

Predicting fatigue life of composite materials is essential to increase reliability of manufacturing systems. The predicting techniques for fatigue life of composite materials are not widely investigated. The support vector regression (SVR) is an emerging forecasting technique and has been applied in...

This paper proposes a class of nonlinear stochastic volatility (SV) models based on the Box-Cox transformation. The proposed class encompasses many parametric SV models that have appeared in the literature, including the well known lognormal SV model, and has an advantage in the ease with which different...

In large vehicles such as a train, passengers can access Internet through an in-vehicle mobile router to effectively reduce the cost and overhead of roaming to a new network. While we apply the idea of mobile network into large vehicles, the critical issue is how to build up seamless Internet access...

For the overheads of 802.11 WLAN, several frame aggregation mechanisms had been proposed to deal with this shortcoming. Since the rare consideration of QoS in these proposals, we took advantage of 802.11e queueing model to enhance the priority scheduling. This paper approaches to eliminate the decomposition...

Due to the rapid grow up of transaction volume of derivatives in the financial market, the Black-Scholes options pricing model (BSM) is played an important role recently and widely applied in various options contract. However, this theoretical model limited by the influences of many unexpected real world...

This paper presents a framework and tools for modeling and simulating societies as complex systems. Although the concept of the complex systems has been highly demanded in social sciences, there is no satisfactory scheme for modeling and simulating it. In this paper, we propose the model framework, which...

This paper extends the dynamic programming, utility maximization model proposed by Wang (2004) to value an investment opportunity whose income streams follows a regime-switching process in incomplete markets. Specifically, the model is applied to solve for certainty equivalent of an investment opportunity...

This study develops inter-temporal dynamic asset allocation with stochastic volatility (DAASV) models. The DAASV models integrate the stochastic volatility feature inherent in asset returns into the allocation procedure. By applying the DAASV, an investor can more efficiently diversify the unsystematic...

The convergence of estimators, e.g., maximum likelihood estimators, for increasing sample size is well understood in many cases. However, even when the rate of convergence of the estimator is known, practical application is hampered by the fact, that the estimator cannot always be obtained at tenable...

The significant jump in world crude oil price over the past year has raised great concern over the economic impact that such a price shock may bring about on Taiwan’s economy, which has been characterized by extremely high import-oil dependence. Previous analyses have been tackling similar issue from...

In 1980s, many empirical researches’ findings (i.e., Shiller(1984), Thaler (1985) et al. ) did not support efficient market hypothesis (EMH). Previous studies (e.g., Bernartzi and Thaler, 1995) related to behavioral model suggest that certain market anomalies are consistent with the presence of irrational...

In this paper, we studied complexity and entropy density of stock market by modeling epsilon-machine of Korean Composition Stock Price Index (KOSPI) from year 1992 to 2003 using causal-state splitting reconstruction (CSSR) algorithm.

This paper proposes the pricing formula of sequential compound options (SCOs) with random interest rate and the applications call Milestone Project Valuation (MPV). Most compound options in literatures are 2-fold with constant parameters through time. The multi-fold compound options are just sequential...

The Black-Scholes options pricing model (BSM) is limited by the influences of many unexpected real world phenomena caused due to its six unreasonable assumptions, which often make the miss-pricing result because of the difference of market convention in practical. If we were to soundly take these phenomena...

M&A and green field investment (GFI) are very important methods of company growth. Each of the investment ways could bring different outstanding achievement and development of company, so it is very important to choose the way of investment. This paper discusses the boundary of M&A and green field investment...

The prospect theory implies that the inclusion of a gain-lock-in device into the floor of portfolio insurance can benefit the long-term asset management under loss aversion. We find that the relaxation of the multiple of the CPPI from a constant to a dynamic can improve the performance in the short-term....

In 2005, Sun, Hsieh, and Hwang proposed two secure e-mail protocols with perfect forward secrecy. In the first protocol, the authors apply smart card and Diffie-Hellman key agreement scheme to achieve the perfect forward secrecy. However, due to it requires a smart card to store some parameters, it is...

Web service is very important for both e-commerce and e-government. However, web service process based on syntax level can’t deal with some user query very effectively. In order to make user get more information on the internet, semantic web is presented and a lot of related research results have been...

Object correlations are common semantic patterns in virtual reality systems. They can be exploited for improving the effectiveness of storage caching, prefecthing, data layout, and minimization of query-response times. Unfortunately, this information about object correlations is unavailable at the storage...

Fuzzy distance is applied on data analysis, classification, and production positioning analysis widely. In this paper, We introduction a fuzzy distance by using graded mean integration representation of generalized fuzzy number and the span of fuzzy number, We also discuss the distance of the linguistic...

This paper presents the nano-positioning control of a piezoelectric platform. A Bouc-Wen model is established to describe the nonlinear hysteretic effect of piezoelectric systems. Three kinds of compensators, traditional PI controller, PI-like fuzzy logic controller (FLC) and adaptive PI-FLC controller,...

In this paper, we extend research done in max-min fuzzy neural networks in several important ways. We replace max and min operations use in the fuzzy operations by more general t-norms and co-norms, respectively. In addition, instead of the Łukasiewicz equivalence connective used in the network of Reyes-Garcia...

A novel hybrid C+L band EDFA/RFA is designed to share the 1480 nm pump laser(s). The concepts are based on three-level amplification mechanism for the C band EDFA and Raman shift amplification mechanism for the L band RFA, respectively. It has the advantage to simplify the pump source design. The optimum...

We report the investigation of ring cavity tunable laser, which is based on FBG technology. The laser linewidth, power variation and tuning range are 0.015 nm, 0.5 dB and 31.0 nm, respectively. The ring-cavity tunable laser also has 60 dB of SMSR to insure high-quality operation. With the features mentioned...

New coplanar waveguide (CPW) filters with a fork-shaped defected ground structure (DGS) are proposed for radio-frequency (RF) and microwave applications. The miniature CPW DGS filters developed are based on the silicon technology. The filters are able to provide the bandstop characteristics with high...

A new optical device for wavelength auto-router was proposed. Such a structure is useful in the integrated-optic for optical operation and data communication. We use the finite-difference beam propagation method to investigate the phenomenon of the proposed numerical model.

This investigation examines all-optical multicast routing in wavelength-routed optical networks with sparse Multicast Capable (MC) nodes that have three phases. The first phase is the MC node placement, and the maximum path count first (MPCF) algorithm is utilized to obtain candidates for MC nodes. The...

This paper examined bankruptcy predictive accuracy of five statistics models--discriminant analysis logistic regression, probit regression, neural networks, support vector machine (SVM), and genetic-based SVM (GA-SVM) that influenced by variable selection. Empirical results indicate that the SVM-based...

Security Exchange Commission in Taiwan requires all public companies to file and announce their monthly sales figure by the of the following month. This requirement has established another channel for market investors to obtain additional accounting information on a more timely basis than quarterly or...

Knowledge management (KM) is suggested as a method to manage and apply knowledge for business management. In this paper, we suggest a framework based on OPF (Open Process Framework) meta model for the knowledge-based decision-making. Based on the modeling method of OPF, we can translate partial and implicit...

Most routing protocols focus on obtaining a workable route without considering network traffic condition for a mobile ad hoc network (MANET). Therefore, the quality of service (QoS) is not easily achieved by the real time or multimedia applications. To support QoS, this work proposes a QoS-aware routing...

In the security infrastructure, intrusion detection has become an indispensable defense line in face of increasing vulnerabilities exposed in today’s computing systems and Internet. In this paper, our approach uses ontologies as a way of grasping the knowledge of a domain, expressing the intrusion detection...

Censoring models are frequently employed in reliability analysis to reduce experimental time. There are three censoring model: type-I, type-II and random censoring. In this study, we focus on the right-random censoring model. In the previous literature, an imputation of the censored observation is considered...

String matching of a large string collection on mobile devices has been a difficult problem because of the memory space and computing speed constraints. We propose a method to efficiently determine whether a query string exists in the large string collection. The proposed method, based on a string encoder...

Quantum-dot cellular automata (QCA) provide a novel electronics paradigm for information processing and communication. A basic quantum-dot cell consists of several quantum dots with two excess electrons. A binary coded decimal (BCD) and a decimal coded binary (DCB) circuit based on QCA logic gates: the...

This study attempts to find the possibility of making relatively higher profit with lower risk when trading futures commodities. The system applies XCS classifiers to explore the rules of spread trading of these commodities. Our simulation holds a trading strategy that in every transaction, the proposed...

The purpose of this empirical study is intended to investigate XCS (Extended Classifier System) based model with knowledge rules for dynamic TIPP (Time Invariant Portfolio Protection) policy. There are two XCS-based agents in the proposed model (MA-TIPP).One agent dynamically optimizes Multiple and Tolerance...

A hybrid BPNN-weighted GREY-C3LSP prediction (BWGC) is used for resolving the overshooting phenomenon significantly; however, it may lose the localization once volatility clustering occurs. Thus, we propose a compensation to deal with the time-varying variance in the residual errors, that is, incorporating...

We provide a framework for learning risk-neutral measures (Martingale measures) for pricing options from high frequency financial data. In a simple geometric Brownian motion model, a price volatility, a fixed interest rate and a no-arbitrage condition suffice to determine a unique risk-neutral measure....

In this paper, we replicate Nelson-Winter model in order to analyze the inter-enterprise competition from the perspective of economic change. For this purpose, we build the simulation model as Multi-Agent-Based Simulation in PlatBox Simulator. By replicating the Nelson-Winter model, which clarifies the...

This paper provides the most complete evidence to date on the importance of monetary aggregates as a policy tool in an inflation forecasting experiment. Every possible definition of ‘money’ in the USA is being considered for the full data period (1960 – 2006), using the most sophisticated non-linear...

Stock data mining such as financial pairs mining is useful for trading supports and market surveillance. Financial pairs mining targets mining pair relationships between financial entities such as stocks and markets. This paper introduces a fuzzy genetic algorithm framework and strategies for discovering...

The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic...

In this paper we adopt the Markov-switching specification to establish the hybrid model with time-varying loading on each of chartist and fundamentalist techniques. The US dollar exchange rates of four Asian tiger countries’ currencies serve as the representative examples in this paper. Our empirical...

Most of GA-based portfolio assets allocation uses normalization method to allocate investment asset’s weight. However, the normalization process will cause unease converging and even diverging characteristics, because it changes the gene’s relativity of address in chromosome. In this paper, we propose...

Artificial intelligence decision support system is always a popular topic in providing the human user with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is to compare different methods of artificial intelligence decision...

This paper outlines a data mining approach to analysis and prediction of the trend of stock prices. The approach consists of three steps, namely partitioning, analysis and prediction. A modification of the commonly used k-means clustering algorithm is used to partition stock price time series data. After...

This paper uses data from Taiwan’s banking sector to investigate if state-owned banks can serve as an internal regulation mechanism to sustain market competition. In contrast to the traditional second-best literature, the evidence shows that a certain degree of market coordination exists in the industry,...

As everyone knows, multiple regression analysis is an important approach to prediction studies. However, regression model has some limitations and constraints in the real world practices. This study applied fuzzy regression using neural network (FRNN) to predict organizational performance, and the findings...

A novel training paradigm for artificial neural networks had been developed and presented in this article. In the proposed approach, a revised version of particle swarm optimization (PSO) had been employed to find out the optimal connection weights of feed-forward artificial neural networks for given...

GARCH model has a long history and permeates the modern financial theory. Most researchers use several thousands of financial data and maximum likelihood to estimate the coefficients of model. Statistically, more samples imply better estimation but are hard to obtain. How many samples are sufficient...

In order to be competitive in the semiconductor manufacturing industry, quality improvement and yield enhancement have received increasing attention. The research focuses on the molding process of Integrated Circuit (IC) assembly. The defects often occurred in molding process include hole, vein, crack,...

we propose a hybrid decision model for supporting the ranking financial status of corporations using case-based reasoning augmented with genetic algorithms and the fuzzy nearest neighbor method. An empirical experimentation on 746 cases was conducted that shows that the average accuracy of the ranking...

Concept hierarchies are important for generalization in many data mining applications. We propose a method to automatically build a concept hierarchy from a provided distance matrix. The method is a modification of traditional agglomerative hierarchical clustering algorithm. When two closest clusters...

In this paper, we propose a new genetic algorithm based on the two-dimensional encoding method. Appropriate two-dimensional crossover and mutation operations are designed based on the two-dimensional representation to generate the next generations. A two-dimensional repairing mechanism is also proposed...

A major failure of rational models (cognitive science, game theory) of organizations is the use of static concepts of interdependence to predict dynamic behavior. A quantum model of organizations transforms the traditional model with its dynamic interdependence of uncertainty. We consider field and laboratory...

Investors’ overconfidence and regret aversion lead to behavioral biases, such as over-reaction、under-reaction and disposition effect. By constructing a numerical simulation model, this paper shows that, return distributions under the behavioral biases have higher peaks and fatter tails, and they are...

The main objective of this study is developing a linguistic cluster model in order to meet the public security index requirement and extract crime rule in time series. In contrast to the current studies in crime theory which mostly rely on traditional behavior science, we turned to a hybrid approach...

Information technology (IT) has been extensively adopted in banking industries. The reasons for this massive adoption of IT are mainly twofold: for individual banks, IT can reduce banks’ operational costs (the cost advantage), and facilitate transactions among customers within the same network (the network...

Most researches have focused on the use of document feedback or factor analysis as metrics for financial distress prediction. The theoretical basis for the former is relatively weak, while the latter is severely limited by data requirements. As such, this paper will instead use grey relation analysis...

A general phenomenon puzzles all investors is that on one hand, most individual investors believe they need to construct the portfolio consisting of 15 or more stocks to prevent risk because that large investment companies frequently get high returns is due to they obey the existing investment theory...

As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies...

The medical care industry has been dramatically developed in the last two decades in Taiwan and it has resulted in an extremely risky position. The purpose of the research was the development of a neural network model to recognize profitable customers for dental services marketing. Data set was built...

With the development of computer graphics and virtual realities, the demand for a content-based 3D model retrieval system becomes urgent. In this study, two features, grid sphere and dodecahedral silhouettes, are proposed and combined for 3D model retrieval. The experiments are conducted on a 3D model...

We propose a new feature selection procedure based on a combination of a pruning algorithm, Apriori mining techniques and fuzzy C-mean clustering. The feature selection algorithm is designed to mine on a multiresolution filter bank composed of rotationally invariant moments. The numerical experiments,...

A finger finding procedure has been presented to recognize the finger number of the hand gesture. The hand gesture is extracted from the stationary background and transformed into a binary image. The hue attribute, that is, the I value in the YIQ color space is used to extract the hand gesture shape....

This paper proposed an effective and robust method to detect the rare behavior events within the compressed video directly. New motion feature called object-based accumulative motion vector (OAMV) is generated to extract a prominent motion feature and then polar histograms are used to describe the distribution...

This paper presents a novel approach to natural scene segmentation. It uses both color and texture features in cooperation to provide comprehensive knowledge about every pixel in the image. A novel scheme for the collection of training samples, based on homogeneity, is proposed. Natural scene segmentation...

Generalized Lloyd Algorithm(GLA) is important in vector quantizer design. It runs fast, but it is sensitive to initial conditions and it may find a local optimum. We propose an improved approach based on GLA, named vector quantized codebook reorganization algorithm (VQCRA). VQCRA finds better codebooks...

As a new general machine-learning tool based on structural risk minimization principle, Support Vector Machines (SVM) has the advantageous characteristic of good generalization. For this reason, the application of SVM in fault diagnosis field has becomes one growing reach focus. In this paper, data fusion...

This paper proposes a new approach for tracking the contour of moving object for head-shoulder video sequence using initial shape model. First, we can utilize manual process or some segmentation approach to obtain the initial shape model. Then, we detect the changing ratio of intensity outside the bounding...

The purpose of this research is to use the visual inspection technique for the automatic tool wear measurement of different coated drills. The tool wear images with the different coated drilling are captured using a machine vision system incorporating with an effective vertex detection algorithm based...

Due to the flood of pornographic web sites on the internet, content-based web filtering has become an important technique to detect and filter inappropriate information on the web. This is because pornographic web sites contain many sexually oriented texts, images, and other information that can be helpful...

In this paper we present a novel dense matching algorithm that relies on sparse stereo data in order to build a dense disparity map. The algorithm uses a recursive updating scheme to estimate the dense stereo data using various interpolation techniques. The major problem of classical template matching...

Correct classification of various kinds of scenes in sport videos is essential for higher-level content analysis such as event detection. The paper presents a novel technique for the classification of the typical scenes of baseball videos. The spatial color features are employed to detect pitch scene...

SIGNATURE RECOGNITION USING CONJUGATE GRADIENT NEURAL NETWORKS Transforming the input before training yields much lower error, but is more sensitive. Most importantly, we have presented system can vary in security depending on the situation. Uses for such a system range from securing a credit card transaction...

A method to analyze and assess knowledge sharing risks in the virtual enterprise is proposed. Firstly, based on risks analysis, an index system is set up to assess such risks as the core competence losing risk, the enterprise culture risk, the knowledge spillover effect risk and the moral risk, etc.....

The portfolio optimization model, initially proposed by Markowitz in 1952 and known as mean-variance model (MV model), is applied to find the optimized allocation among assets to get higher investment return and lower investment risk. However, the MV model did not consider some practical limitations...

This paper introduces the least absolute deviation estimators to construct an interval regression model, having interval output and crisp input data when the data contains interval outliers.

In this paper we introduce a practicable system by combining a vision processing algorithm and a fuzzy controller to obtain an efficient active tracker. Target tracking performance is heavily dependent on a good blend of vision algorithm and control. Because of performance and computational complexity,...

Most decision-making and problem-solving tasks are too complex to be understood quantitatively. People perform such tasks using knowledge that is imprecise rather than precise. This study presents consistent fuzzy linguistic preference relations rather than fuzzy analytic hierarchy process (FAHP) to...

Based on the fuzzy set theory, this study introduces three novel three-phase fuzzy feeder models for fast distribution system calculations. These fuzzy models are formulated using three lumped individual phase loads to represent single-phase, three-phase unbalanced, and nonuniformly distributed loads...

Once the input values are given, the active rules in a fuzzy inference execution have been determined. Based on the observation, our approach is to identify the active rules before fuzzy inference execution. To achieve this goal, our architecture provides the following two mechanisms: (1) a mechanism...

In this paper, we present a search model, which divide symptoms into two sets, i.e., the positive symptom set (J1) and the negative symptom set (J2), to eliminate the causes of low possibility in the cause set to more effectively find various possible breakdown causes occurred during spinning process....

The paper deals with fuzzy attribute logic (FAL) and shows its completeness over all complete residuated lattices. FAL is a calculus for reasoning with if-then rules describing particular attribute dependencies in object-attribute data. Completeness is proved in two versions: classical-style completeness...

We present Pavelka-style fuzzy logic for reasoning about attribute implications, i.e. formulas $A\Rightarrow B$. Fuzzy attribute implications allow for two different interpretations, namely, in data tables with graded (fuzzy) attributes and in data tables over domains with similarity relations. The axioms...

The teachers and the school authorities often call the parents in connection with a child’s ‘performance’ in school. The children have to face the wrath of both the parents and the teachers. This tension slowly builds up and the child decides to quit the school forever. This paper analyzes the causes...

In this paper, a comparison study for the non-stationary power signal prediction by using several neural models is presented. A reliable and accurate neural forecasting model is trying to be found and concluded. This study is expected to provide some suggestions and could be treated as a reference for...