A neural network architecture for implementation of expert systems for real time monitoring

Since neural networks have the advantages of massive parallelism and simple architecture, they are good tools for implementing real time expert systems. In a rule based expert system, the antecedents of rules are in the conjunctive or disjunctive form. We constructed a multilayer feedforward type network in which neurons represent AND or OR operations of rules. Further, we developed a translator which can automatically map a given rule base into the network. Also, we proposed a new and powerful yet flexible architecture that combines the advantages of both fuzzy expert systems and neural networks. This architecture uses the fuzzy logic concepts to separate input data domains into several smaller and overlapped regions. Rule-based expert systems for time critical applications using neural networks, the automated implementation of rule-based expert systems with neural nets, and fuzzy expert systems vs. neural nets are covered

A neuro-fuzzy architecture for real-time applications

Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach

Automated implementation of rule-based expert systems with neural networks for time-critical applications

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed

A new approach for designing self-organizing systems and application to adaptive control

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed

On the stranding of sea cow Dugong dugon at Mandapam along the Gulf of Mannar coast.

A dead male sea cow Dugong dugon (Muller) measuring 194 cm in total length and about 125kg in weight was stranded along the Gulf of Mannar coast at Mandapam.The morphometric measurements of specimen were taken and identified to species level

Closed Form Solution for Parabolic Flow of a Inclined Isothermal Plate With Uniform Mass Diffusion

The fluid flow across an unbounded horizontal plate embedded with uniform mass diffusion is studied in this article together with the impacts of the chemical reaction and parabolic motion, while the temperature and concentration of the plate remain constant. Using initial and boundary conditions, partial differential equations were used to describe this phenomenon. Introduce some appropriate non-dimensional variables and utilize the Laplace transform method to solve the corresponding dimensionless equations. The following analytical remedies for heat, velocity and concentration profiles were produced in terms of exponential and (erfc) complementary error functions. A MATLAB programme is used to exhibit the results as graphs for various parameters. By creating graphs, we may assess the characteristics of the velocity, Heat and concentration while also studying the physical aspects for various factors

Chemical Reactive Flow past a Parabolic Vertical Plate with Exponentially Accelerated Temperature and Uniform Mass Transfer

The topic of flow across an infinitely wide parabolic vertical sheet with accelerating reactions of chemicals and heating is addressed in this article. The Laplace transform method is used to rectify the dimensioned equations that govern of movement into a set of non-dimensional regulating mathematical equations of motion. It is found that thermal energy as well as chemical responses have a substantial impact on the rates of both mass and heat transmission. Using analytical formulas, create temperatures, concentrations, and velocity personas. The physical aspects of various components, including acceleration (a), thermal radiation parameter (R), chemical reaction parameter (K), thermal Grashof number (Gr), mass Grashof number (Gc), Schmidt number (Sc), Prandtl number (Pr), and time variable (t) are investigated. By drawing graphs, characteristics of the velocity, temperature, and concentration are examined

Phase-alternated composite π/2 pulses for solid state quadrupole echo NMR spectroscopy

Phase-alternated composite π/2 pulses have been constructed for spinI=1 to overcome quadrupole interaction effects in solid state nuclear magnetic resonance (NMR) spectroscopy. Magnus expansion approach is used to design these sequences in a manner similar to the NMR coherent averaging theory. It is inferred that the symmetric phase-alternated composite π/2 pulses reported here are quite successful in producing quadrupole echo free from phase distortions. This effectiveness of the present composite pulses is due to the fact that most of them are of shorter durations as compared to the ones reported in literature. In this theoretical procedure, irreducible spherical tensor operator formalism is employed to simplify the complexity involved in the evaluation of Magnus expansion terms. It has been argued in this paper that composite π/2 pulse sequences for this purpose can also be derived from the broadband inversionp pulses which are designed to compensate electric field gradient (efg) inhomogeneity in spinI=1 nuclear quadrupole resonance (NQR) spectroscopy

On the stranding of sei whale, Balaenoptera borealis Lesson at Mandapam along the Palk Bay coast

On 20th January, 1992, an adult female sei whale, measuring 14.0 m in total length and weighing about 10 tonnes stranded at Theedai near the marine fish farm of Central Marine Fisheries Research Institute, Mandapam Camp

Coupled-barrier diffusion: the case of oxygen in silicon

Oxygen migration in silicon corresponds to an apparently simple jump between neighboring bridge sites. Yet, extensive theoretical calculations have so far produced conflicting results and have failed to provide a satisfactory account of the observed $2.5$ eV activation energy. We report a comprehensive set of first-principles calculations that demonstrate that the seemingly simple oxygen jump is actually a complex process involving coupled barriers and can be properly described quantitatively in terms of an energy hypersurface with a ``saddle ridge'' and an activation energy of $\sim 2.5$ eV. Earlier calculations correspond to different points or lines on this hypersurface.Comment: 4 Figures available upon request. Accepted for publication in Phys. Rev. Let