A computer aided facility management systems are now used extensively in many areas such as maintenance of electric power equipment. However most of these systems possess data management structures that deal with only 2 dimensional space. The 3D graphic system that enables users to explore the 3D space interactively and examine 3D spatial views of the environments would be very useful for facility management. In this paper, we describe about a facility managememt system based on computer generated 3D virtual city environment. This prototype system supplies the user interactive operations even if the virtual city is very large. Moreover, this system can deal with not only 3D spatial information but also temporal information. Using this system, the user can get the facility management environment that is very useful for management, analysis and planning etc.
This paper examines the simulation system for negotiation support based on the concept of genetic algorithms. Its purpose is to support negotiators for agreement by giving them some rational compromise in practice. Negotiators here mean constituents of a group, each of whom posesses a different opinion and view but has a common goal. Actually in this model negotiators' decisions are made first according to utility theory in advance and then compromise is to be attempted by modifying the utility function. Based on this, the modification is carried out by utilizing the searching function of genetic algorithms to suggest the way of attaining the compromise point in a negotiation. In this case, the parents group as objects of genetic operations consist of every individual but contradicts the compromising process. Fitnesses of each individual are to be set up according to the degree of dependence on the process. As a concrete example of the simulation, group car buying decision is dealt with for showing its actual process and the results. From the above, it can be deduced that this system suggests negotiators a most efficient and suitable solution.
Using PARTHENON, a CAD (Computer Aided Design) software system, we design five kinds of fixed point divider, one floating point divider, and synthesize their logic circuits. We compare our designed circuits in point of the numbers of gates, area, power consumption and the maximum of rising delay. As a results, in case of fixed point division circuits, the gate numbers in each circuits is expressed with their division bits and different variables. The delay time increase depends on the division bits increase, but its increasing rate is difference by different circuits. The floating point divider was implemented by index calculation, extra process, rounding process to the fixed point divider. The delay time in the floating point divider is longer than that in the fixed point divider only by the amount of time needed to perform the added process.
A distribution line carrier communication have merits in no need of dedicated communication lines. But a transmission data rate of existing practical systems in phase-to-phase coupling is 60bps and it is low. In order to realize high speed rate we measured signal transmission characteristics of actual disribution systems from 1kHz to 10kHz and compared them with calculation values. Also we measured noise characteristics in distribution lines, simulated a signal to noise ratio in PSK modulation and studied the possibility of practical high speed data transmission. As the results, it is possible to get S/N 20db, and bit error rate of 10-5 or less for 1200bps data transmission rate, in case that transmitting power is 20V per one phase, carrier frequency of 3kHz up to 4kHz, if the countermeasure to near phase advance capacitor is applied.
This paper presents a new method to find personal characteristics of signatures using a genetic algorithm. The new method uses a new coding method, a new crossover method, and a genetic algorithm with a local improvement mechanism. The new coding method is devised for finding personal characteristics from signatures. The new crossover method determines the number of characteristics used for the signature verification. The genetic algorithm is very efficient in improving the local portions of chromosomes. Experiments are done to show that the personal characteristics are efficiently found by the proposed method.
This paper proposes a new method for extracting the sensibility (kansei) of human experts, and applies it to the design of a pearl color evaluation system. A factors identification method using sensitivity of layered neural networks finds the influential factors as the input units which have the greatest influence on all outputs. This method has been applied to the network mapping between spectral reflectance of pearls and the pearl color categories evaluated by experts, and allowed some specific wavelength bands to be identified as the essential factors contributing to the evaluation. Based on this result, a pearl color evaluation system has been designed using multi-bands images (MBI) acquired by combining a monochrome CCD camera with several interference filters corresponding to the identified major wavelength bands factors. Moreover, the identification method has been applied to find the influential factors of each image of MBI and finally the experimental results of discrimination using those factors show that this system is able to give evaluations of pearl color successfully as an expert does.
The advent of digital video disks (DVD) has lead to narrower tracks along with a demand for higher density in the field of optical disks. This general and recent trend requires the improvement of follow-up capability within limits which are not detrimental to stability and speed of response. We have developed a new adaptive repetitive control system that can improve follow-up capability by applying repetitive control theory to tracking control, and which can change the learning capacity according to such nonperiodic components as insufficient stability margin (one of the problems in repetitive control), disk drive vibration and disk defects, in response to the degree of track correlation. Furthermore, the division of the learning portion into two stages, namely long-term and short-term storage memories, compensates for the short-term memory being degraded by insufficient correlation and enhance the learning capability when disturbance occurs. As a result we were able to reduce the track error by disk eccentricity down to 0.02μm or less in a DVD disk with an eccentricity similar to compact disks (CD), and can confirm that the disk functions in a stable fashion even with interference from irregular disturbances.
A new method is presented for model reference adaptive control of MIMO (multi-input multi-output) nonminimum phase discrete-time systems using approximate inverse systems. It is shown that unstable pole-zero cancellation can be avoided using this method. Finally, computer simulation results are presented to illustrate the effectiveness of the proposed method.
A status selection planning system is one of planning expert systems. In this system, the most promising status from tentative statuses generated by applying the dispatching rules is selected by a status selection rule. Dispatching rules mean fragmentary and convenient assignment algorithms. Quality of the solution depends on the knowledge-base. However, it is usually difficult to acquire useful knowledge from human experts. In this paper, a learning method of a status selection rule set using GA (Genetic Algorithm) is proposed. The status selection rule set is regarded as an individual. The representation of scheduling knowledge by gene is generally difficult in GA, because it is necessary to carry out crossover operation on gene. To cope with the representation problem, a status selection rule is represented by tree construction and a status selection rule set is represented by a list of those tree construction. From the results of the application to a simple job shop problem, it is shown that the knowledge acquired by the proposed method is superior to the human's knowledge
This paper presents a distributed algorithm for minimizing a nonconvex multimodal function. The local search methods based on the gradient information have efficient convergence property, but these methods have a tendency to get stuck at a local minima. Therefore a global optimization method with good convergence property is desired. Although many global optimization methods such as Simulated Annealing and Tree Annealing have been proposed, these methods require much computational cost. In recent years, new distributed algorithms based on Artificial Life (ALife) is studied and its potential power is reported. In this paper, therefore, the frame work of ALife is employed into a function minimization. Since the proposed method utilizes no gradient information, it can be applied to very wide class of problems. In this paper, firstly, ALife in the two-dimensional discrete system is realized. Then it is extended to the multi-dimensional continuous system. Next, ALife is applied to an optimization problem of function minimization. The effectiveness of the proposed method is demonstrated through some numerical tests on multimodal test functions. The numerical tests also show that the proposed method is superior to the Simplex method and Tree Annealing method.
This paper proposes a new approach to distribution system planning. Planning of distribution system configuration tries to determinate a route from each power source to each load under conditions of satisfying all power demand and no overload of equipment. Load balancing and switching control play important roles to fulfill these requirements. This planning could be formulated as a large scale combinatorial problem to which system theory is difficult to apply so that a new approach, genetic algorithm, has been applied to the problem. Candidates of a final solution are expressed by chromosomes. Modifications of a canonical genetic algorithm are introduced to minimize infeasible chromosomes that do not satisfy network constraints when the algorithm creates next generation. These modifications have improved performance of the algorithm and the proposed method has proved to be effective. In additional to that, object-oriented analysis is used to make models of distribution system and the genetic algorithm. As a result, the proposed method gives various kinds of flexibility and reusability.
Described is an optical fiber control signal transmission system in which multifrequency control signals used as parallel control signals are transmitted from the sender to the receiver through the optical fiber. In accordance with the multiplexing of up to 8 sinewave signals at 65kHz, 110kHz, 210kHz, 310kHz, 410kHz, 510kHz, 610kHz, and 710kHz, 8-bit multifrequency signals are formed, and then combined together by the mixer. The multifrequency signals are fed to the squarewave FM modulator to modulate them by squarewave frequency modulation (SWFM) scheme. The SWFM signal is fed to the LED to accomplish optical intensity modulation (IM). The multifrequency signals which are transmitted through the GI mode optical fiber in a distance of up to 2km are detected using a set of bandpass filters and F/V converters. Based on the concept of the multifrequency control signal generation and the SWFM-IM modulation scheme, the optical fiber control signal transmission system has a capability to transmit the SWFM-IM signal over a distance of 2km with a group delay time of less than 100μs.