Showing papers in "Information Sciences in 2000"

TL;DR: The main motivation for this design was to control some known nonlinear systems, such as robotic manipulators, which violate the conventional assumption of the linear PID controller.

TL;DR: This paper combines quantum computation with classical neural network theory to produce a quantum computational learning algorithm that produces an exponential increase in the capacity of the memory when compared to traditional associative memories such as the Hopfield network.

TL;DR: The paper presents a transition from the crisp rough set theory to a fuzzy one, called Alpha Rough Set Theory or, in short, a-RST, which leads naturally to the new concept of alpha rough sets which represents sets with fuzzy non-empty boundaries.

TL;DR: Using five chaotic time series functions, empirically compares a genetic algorithm with backpropagation for training NNs using the chaotic series because of their similarity to economic and financial series found in financial markets.

TL;DR: A unified systematic framework for designing dynamic feedback controllers for nonlinear systems described by Takagi–Sugeno (T–S) models is presented, which can be applied to hybrid or switching systems.

TL;DR: A rule induction system based on rough sets and attribute-oriented generalization is introduced and was applied to a database of congenital malformation to extract diagnostic rules and an expert system which makes a differential diagnosis on congenital disorders is developed.

TL;DR: This paper addresses the problem of matching records which refer to the same entity by computing their similarity by deploying advanced data-mining techniques for dealing with the high computational and inferential complexity of approximate record matching.

TL;DR: The results of this approach indicate that the use of neural clustering using a type 2 representation can improve the classification of shin images.

TL;DR: Experimental and simulation results show that the proposed fuzzy controller yields the optimal disturbance rejection performance and the desired transient response characteristics of the Takagi–Sugeno model based fuzzy control systems.

TL;DR: The overall system includes a complete user–machine interface, motor control modules and safety and autonomous guidance systems that are adaptable to the particular needs of each user according to the type and degree of handicap involved.

TL;DR: The α-resolution principle, which is based on lattice-valued propositional logic LP(X) with truth-value in a logical algebra – lattice implication algebra, is investigated and established, and the theorems of both soundness and completeness of this α- resolution principle are proved.

TL;DR: A novel general-purpose nonlinear PID controller realized via fuzzy PID control that uses the authors' newly-introduced simplified Takagi‐Sugeno (TS) rule scheme and the results show that the fuzzy PID controller significantly outperforms its linear counterpart, and is safer and more robust over a wide range of patient condition.

TL;DR: A safe system architecture for the Bremen Autonomous Wheelchair is proposed and a hierarchy of low level application modules is presented, and a route navigation approach that provides a high level of support is described in detail.

TL;DR: This paper introduces and study the concepts of strongly λ-summable and κ-statistical convergence, and studies the relationships between these concepts and theorems in LaSalle's inequality.

TL;DR: The space of bounded difference sequences of fuzzy numbers has been discussed and it is shown that fuzzy numbers can be partitioned into bounded difference subsequences and fuzzy numbers.

TL;DR: The paper presented has solved the problem under which additional assumptions a given closure operator can be represented by an upper approximation within the concepts of rough set theory.

TL;DR: Novel parameter tuning algorithms are obtained that are similar to ϵ-modification in the case of continuous-time adaptive control and uniform ultimate boundedness of the tracking error and the fuzzy parameter estimates are presented.

TL;DR: Some invariant characters of an information system under a homomorphism are discussed and their importance in the field of artificial intelligence is discussed.

TL;DR: Three fuzzy control modules, namely, line, assembly, and disassembly controller, are developed to keep the work-in-process (WIP) inventory and cycle time at low levels, along with high machine utilization and throughput.

TL;DR: The versatility of the proposed architecture (which supports practically any kind of collaborative application) and its recursive replication at all levels of resolution within the collaborative application are illustrated on a supply-chain example.

TL;DR: Evidence from neuroscience and quantum computing theory in support of the notion of autonomy in the workings of cognitive processes is reviewed to show how cognitive behavior is not based just on incoming sensory data.

TL;DR: Five criteria of FA words are defined for hierarchical fields and a method of extracting shorter FA words of compound words is proposed, estimated by the simulation results of 140 fields' text files.

TL;DR: This paper proposes a hierarchical object-oriented Petri net (HOONet), and demonstrates the usefulness of HOONet by applying it to modeling and analysis with an example.

TL;DR: Three tuple transmission approaches that can be used to determine the transmission time of tuples in the answer set of a location-dependent CQ are proposed and the relative performance of the proposed approaches under different settings of environmental parameters is evaluated.

TL;DR: It is proved, in a constructive manner, that the general n-dimensional hierarchical fuzzy systems are universal approximators.

TL;DR: This paper presents basic notions of discrete-time software reliability modeling, and proposes three methodologies, i.e., probabilistic, Bayesian and fuzzy, and various corresponding models.

TL;DR: This paper proposes a novel multiple-constraint multicast routing algorithm based on genetic algorithms, called MCMGA, which is evaluated via simulations on different sizes of random graphs and yields solutions of the least cost.

TL;DR: A messy coding scheme for fuzzy rules reduces the size and complexity of the rule base, with the result, that the fuzzy control design remains tractable for the genetic algorithm.

TL;DR: A low-level architecture for distributed process/machine control is described that is dynamically reconfigurable and supports distributed applications based on the IEC-1499 function block (FB) standard.

TL;DR: The research described in this paper combines weighted trigram analysis, clustering, and a special two-pool evolutionary algorithm, to create an Adaptive Information Filtering system with such useful properties as domain independence, spelling error insensitivity, adaptability, and optimal use of user feedback while minimizing the amount ofuser feedback required to function properly.