• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.301-309
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• 2009

A simple and efficient Lambda logic (${\lambda}-logic$) based algorithm is proposed for the solution of the generator constrained economic dispatch problem when the generating units having prohibited zones. The proposed method solves the economic dispatch (ED) problem that takes into account ramprate limits, transmission losses and prohibited operating zones in the power system operation. The proposed method uses a simple heuristic rule based on average power of prohibited operating zones which produces the feasibility of solution for the restricted operating units. The effectiveness of the algorithm is tested on five different test systems and the performance compared with other relevant methods reported in the literature. In all the cases, the proposed algorithm performs better than the previous existing algorithms with a less computational burden.

• Geomechanics and Engineering
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• v.37 no.6
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• pp.599-614
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• 2024

To evaluate the safety status of deteriorated segments in a submarine shield tunnel during its service life, a seepage model was established based on a cross-sea shield tunnel project. This model was used to study the migration patterns of erosive ions within the shield segments. Based on these laws, the degree of deterioration of the segments was determined. Using the derived analytical solution, the internal forces within the segments were calculated. Lastly, by applying the formula for calculating safety factors, the variation trends in the safety factors of segments with different degrees of deterioration were obtained. The findings demonstrate that corrosive seawater presents the evolution characteristics of continuous seepage from the outside to the inside of the tunnel. The nearby seepage field shows locally concentrated characteristics when there is leakage at the joint, which causes the seepage field's depth and scope to significantly increase. The chlorine ion content decreases gradually with the increase of the distance from the outer surface of the tunnel. The penetration of erosion ions in the segment is facilitated by the presence of water pressure. The ion content of the entire ring segment lining structure is related in the following order: vault < haunch < springing. The difference in the segment's rate of increase in chlorine ion content decreases as service time increases. Based on the analytical solution calculation, the segment's safety factor drops more when the joint leaks than when its intact, and the change rate between the two states exhibits a general downward trend. The safety factor shows a similar change rule at different water depths and continuously decreases at the same segment position as the water depth increases. The three phases of "sudden drop-rise-stability" are represented by a "spoon-shaped" change rule on the safety factor's change curve. The issue of the poor applicability of indicators in earlier studies is resolved by the analytical solution, which only requires determining the loss degree of the segment lining's effective bearing thickness to calculate the safety factor of any cross-section of the shield tunnel. The analytical solution's computation results, however, have some safety margins and are cautious. The process of establishing the evaluation model indicates that the secondary lining made of molded concrete can also have its safety status assessed using the analytical solution. It is very important for the safe operation of the tunnel and the safety of people's property and has a wide range of applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2018.06a
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• pp.33.1-33.1
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• 2018

pH is expressed mathematically as $pH=-{\log}[H^+]$, is a measure of the hydrogen ion concentration, [$H^+$] to specify the acidity or basicity of an aqueous solution. The pH scale usually ranges from 0 to 14. Every aqueous solution can be measured to determine its pH value. The pH values below 7.0 express the acidity, above 7.0 are alkalinity and pH 7.0 is a neutral solution. The solution pH can be determined by indicator or by measurement using pH sensor, which measuring the voltage generated between a glass electrode and a reference electrode according to the Nernst Equation. The pH value of solutions depends on the temperature and the activity of contained ions. In nickel electroless plating process, the controlled pH value in some limited ranges are extremely important to achieve optimal deposition rate, phosphorus content as well as solution stability. Basically, nickel electroless plating solution contains of $Ni^{2+}ions$, reducing agent, buffer and complexing agents. The plating processes are normally carried out at $82-92^{\circ}C$. However, the change of its pH values with temperatures does not follow any rule. Thus, the purpose of study is to understand the relationship between pH and temperature of some based solutions and electroless nickel plating solutions. The change of pH with changing temperatures is explained by view of the thermal dynamic and the practical measurements.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.315-323
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• 2000

In this paper, we propose a method of constructing neural networks using bio-inpired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants, Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting nechanism. The DNA coding method has no limitation in expressing the produlation the rule of L-system. Evolutionary algotithms motivated by Darwinaian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it one step ahead prediction of Mackey-Glass time series, Sunspot data and KOSPI data.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.15-17
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• 1994

The economic operation in power systems has long been in keen interests for power system engineers. The classical equal incremental fuel cost rule is still the basis for it, even though more elaborate tools such as optimal power flow have been developed already. The classical method requires usually many iterations, while the optimal power flow shows often some difficulties. This paper suggests a single step solution based on the classical method revisited. The concept is shown graphically. Three sample systems are compared. The proposed approach has shown a single step solution regardless system sizes, while the conventional methods require many iterations.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.191-196
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• 1997

Fuzzy clustering has been playing an important role in solving many problems. Fuzzy c-Means(FCM) algorithm is most frequently used for fuzzy clustering. But some fixed point of FCM algorithm, know as Tucker's counter example, is not a reasonable solution. Moreover, FCM algorithm is impossible to perform the on-line learning since it is basically a batch learning scheme. This paper presents unsupervised learning networks as an attempt to improve shortcomings of the conventional clustering algorithm. This model integrates optimization function of FCM algorithm into unsupervised learning networks. The learning rule of the proposed scheme is a result of formal derivation based on the gradient descent procedure of a fuzzy objective function. Using the result of formal derivation, two algorithms of fuzzy cluster analysis, the batch learning version and on-line learning version, are devised. They are tested on several data sets and compared with FCM. The experimental results show that the proposed algorithms find out the reasonable solution on Tucker's counter example.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.22-31
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• 2015

In this paper, a two-stage hybrid flow shop problem is considered. Specifically, there exist identical parallel machines at stage 1 and two dedicated machines at stage 2, and the objective of the problem is to minimize makespan. After being processed by any machine at stage 1, a job must be processed by a specific machine at stage 2 depending on the job type, and one type of jobs can have different processing times on each machine. First, we introduce the problem and establish complexity of several variations of the problem. For some special cases, we develop optimal polynomial time solution procedures. Then, we establish some simple lower bounds for the problem. In order to solve this NP-hard problem, three heuristics based on simple rules such as the Johnson's rule and the LPT (Longest Processing Time first) rule are developed. For each of the heuristics, we provide some theoretical analysis and find some worst case bound on relative error. Finally, we empirically evaluate the heuristics.

• Geomechanics and Engineering
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• v.17 no.4
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• pp.385-392
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• 2019

The present fractional-order plasticity models for granular soil are mainly established under the triaxial compression condition, due to its difficult in analytically solving the fractional differentiation of the third stress invariant, e.g., Lode's angle. To solve this problem, a three dimensional fractional-order elastoplastic model based on the transformed stress method, which does not rely on the analytical solution of the Lode's angle, is proposed. A nonassociated plastic flow rule is derived by conducting the fractional derivative of the yielding function with respect to the stress tensor in the transformed stress space. All the model parameters can be easily determined by using laboratory test. The performance of this 3D model is then verified by simulating multi series of true triaxial test results of rockfill.