• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.25-33
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• 1997

A DEDS is a system whose states change in response to the occurence of events from a predefined event set. In this paper, we consider the optimal control and reasoning problem for Discrete Event Systems(DES) in the Temporal Logic Framework(TEL) which have been recnetly defined. The TLE is enhanced with objective functions(event cost indices) and a measurement space is alos deined. A sequence of event which drive the system form a give initial state to a given final state is generated by minimizing a cost functioin index. Our research goal is the reasoning of optimal trajectory and the design of the optimal controller for DESs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following ; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.46-51
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• 1997

The optimal control of a continuous process has been performed using genetic algorithms(GAs). GAs are robust and easily applicable for complex and highly nonlinear problems. We introduce the heuristics 'dynamic range' which reduces the search space dramaticaly keeping the robust search of GAs. GAs with dynamic range show the better performance than SQP(Successive Quadratic Programing) method which converges to a local minimum. The proposed methology has been applied to the optimal control of the continuous MMA-VA copolymerization reactor for the production of the desired molecular wieght and the composition of VA in dead copolymer.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.367-380
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• 2019

The paper concerns topology and geometry optimization of statically determinate beams with arbitrary number of supports. The optimization problem is treated as a bi-criteria one, with the objectives of minimizing the absolute maximum bending moment and the maximum deflection for a uniform gravity load. The problem is formulated and solved using the Pareto optimality concept and the lexicographic ordering of the objectives. The non-dominated sorting genetic algorithm NSGA-II and the local search method are used for the optimization in the Pareto sense, whereas the genetic algorithm and the exhaustive search method for the lexicographic optimization. Trade-offs between objectives are examined and sets of Pareto-optimal solutions are provided for different topologies. Lexicographically optimal beams are found assuming that the maximum moment is a more important criterion. Exact formulas for locations and values of the maximum deflection are given for all lexicographically optimal beams of any topology and any number of supports. Topologies with lexicographically optimal geometries are classified into equivalence classes, and specific features of these classes are discussed. A qualitative principle of the division of topologies equivalent in terms of the maximum moment into topologies better and worse in terms of the maximum deflection is found.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.297-300
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• 1997

This paper uses genetic algorithm (GA) for optimal control. GA can find optimal control profile, but the profile may be oscillating feature. To make profile smooth, fuzzy genetic algorithm (FGA) is proposed. GA with fuzzy logic techniques for optimal control can make optimal control profile smooth. We describe the Fuzzy Genetic Algorithm that uses a fuzzy knowledge based system to control GA search. Result from the simulation example shows that GA can find optimal control profile and FGA makes a performance improvement over a simple GA.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.78-84
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• 2006

The objective of this study is to design the optimal die profile that can prevent material fracture in the tube drawing process for automobile steering input shaft. First, the CDV(Critical Damage Value) of material is obtained by the compression test and FE-analysis. The occurrence of fracture is estimated by the FE-analysis considering the CDV. In order to achieve the objective of this study, optimization technique and FE-analysis are applied. FPS(Flexible Polyhedron Search) method, which is one of the non-gradient optimization techniques often used in engineering, is used to search optimal die profile. The drawing die profile is represented by Bezier-curve to generate all the possible die profile. Using FPS method and FE-analysis the optimal drawing die profile is determined. To verify tile effectiveness of the redesigned optimal die, the tube drawing experiment is performed. In the experimental result, it is possible to produce sound product without material fracture using the redesigned optimal die.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

• Journal of KIISE
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• v.44 no.8
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• pp.782-790
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• 2017

The service, 'Hot Search Keywords', provides a list of the most hot search terms of different web services such as Naver or Daum. The service, bases the changes in rank of a specific search keyword on changes in its users' interest. This paper introduces a temporal modelling framework for predicting the rank change of hot search keywords using past rank data and machine learning. Past rank data shows that more than 70% of hot search keywords tend to disappear and reappear later. The authors processed missing rank value, using deletion, dummy variables, mean substitution, and expectation maximization. It is however crucial to calculate the optimal window size of the past rank data. We proposed an optimal window size selection approach based on the minimum amount of time a topic within the same or a differing context disappeared. The experiments were conducted with four different machine-learning techniques using the Naver, Daum, and Nate 'Hot Search Keywords' datasets, which were collected for 2 years.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.467-478
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• 2016

In this paper, we try to find the optimal locations of NeNB(Nomadic evolved NodeB)s for maximizing the overall throughput of the PS-LTE networks. Since finding optimal locations of all NeNBs in a given area is NP-hard(Non-deterministic Polynomial time-hard) problem, we proposed a PSO-based heuristic approach. In order to evaluate the performance, we conducted two experiments. We compared performance with other schemes such as Exhaustive Search, Random Walk Search, and locating neighboring NeNBs with the same NeNB-to-NeNB distance. The proposed method showed the similar results to the exhaustive search method in terms of locating optimal position and user's data throughput. The proposed method, however, has the fast and consistent convergence time.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.3
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• pp.293-303
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• 2015

Optimal design of the water supply pipe network aims to minimize construction cost while satisfying the required hydraulic constraints such as the minimum and maximum pressures, and velocity. Since considering one single design factor (i.e., cost) is very vulnerable for including future conditions and cannot satisfy operator's needs, various design factors should be considered. Hence, this study presents three kinds of design factors (i.e., minimizing construction cost, maximizing reliability, and surplus head) to perform multi-objective optimization design. Harmony Search (HS) Algorithm is used as an optimization technique. As well-known benchmark networks, Hanoi network and Gyeonggi-do P city real world network are used to verify the applicability of the proposed model. In addition, the proposed multi-objective model is also applied to a real water distribution networks and the optimization results were statistically analyzed. The results of the optimal design for the benchmark and real networks indicated much better performance compared to those of existing designs and the other approach (i.e., Genetic Algorithm) in terms of cost and reliability, cost, and surplus head. As a result, this study is expected to contribute for the efficient design of water distribution networks.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1216-1223
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• 2018

As field of application of AMI, AMR uses the power line as the primary means of communication. PLC has a big merit without installation of the new network for communication in a field using the power line which is the existing equipment. However, there is a serious obstacle in commercialization for the instability by noise and communication environment. Therefore, the technical method for maintaining the communication state which overcome such demerit and was stabilized is required essentially. PLC routing technology is applied with the alternative plan now. The routing technology currently managed by field includes many problems by applying the algorithm of an elementary level. PLC routing path search problem can be modeled with the problem of searching for optimal solution as similar to such as optimal routing problem and TSP(Travelling salesman problem). In this paper, in order to search for a PLC routing path efficiently and to choose the optimal path, GA(Genetic Algorithm) was applied. Although PLC was similar in optimal solution search as compared with typical GA, it also has a difference point by the characteristic of communication, and presented the new methodology over this. Moreover, the validity of application technology was verified by showing the experimental result to which GA is applied and analyzing as compared with the existing algorithm.