• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.711-713
• /
• 1996

This paper proposes a unit commitment scheduling method based on Genetic Algorithm(GA). Due to a variety of constraints to be satisfied, the search space of the UC problem is highly nonconvex, so the UC problem cannot be solved efficiently only using the standard GA To efficiently deal with the constraints of the problem and greatly reduce the search space of the GA, the minimum up and down time constraints are embedded in the binary strings that are coded to represent the on-off states of the generating units. The violations of other constraints arc handled by integrating penalty factors. To show the effectiveness of the GA based unit commitment scheduling, test results for system of 5 units are compared with results obtained using Lagrangian Relaxation and Dynamic Programming.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.4
• /
• pp.911-923
• /
• 2016

Machine learning becomes increasingly important in the big data era. Logistic regression is a type of classification in machine leaning, and has been widely used in various fields, including medicine, economics, marketing, and social sciences. Rhipe that integrates R and Hadoop environment, has not been discussed by many researchers owing to the difficulty of its installation and MapReduce implementation. In this paper, we present the MapReduce implementation of Gradient Descent algorithm and Newton-Raphson algorithm for logistic regression using Rhipe. The Newton-Raphson algorithm does not require a learning rate, while Gradient Descent algorithm needs to manually pick a learning rate. We choose the learning rate by performing the mixed procedure of grid search and binary search for processing big data efficiently. In the performance study, our Newton-Raphson algorithm outpeforms Gradient Descent algorithm in all the tested data.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.3
• /
• pp.654-662
• /
• 2016

As the number of gates and basic events in fault trees increases, it becomes difficult to calculate the exact probability of the top event. In order to overcome this difficulty the BDD methodology can be used to calculate the exact top event probability for small and medium size fault trees in short time. Fault trees are converted to BDD by using CUDD library functions and a failure path search algorithm is proposed to calculate the exact top event probability. The backward search algorithm is more efficient than the forward one in finding failure paths and in the calculation of the top event probability. This backward search algorithm can reduce searching time in the identification of disjoint failure paths from BDD and can be considered as an effective tool to find the cut sets and the minimal cut sets for the given fault trees.

• The Korean Journal of Applied Statistics
• /
• v.17 no.3
• /
• pp.459-473
• /
• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• Journal of IKEEE
• /
• v.26 no.2
• /
• pp.240-248
• /
• 2022

Floating-point images that express pixel information as real numbers are used in HDR images. There have been various researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth images and there are only a few number of algorithms applicable to floating-point images, including Gil and Werman's algorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images by improving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that the execution time is improved by about 10% compared to the Kim's algorithm by reducing the redundant work for the repetitively used binary search tree and applying the inverted index.

• Journal of the Korean Society of Safety
• /
• v.30 no.3
• /
• pp.100-106
• /
• 2015

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This quantification generates fault tree solutions such as minimal cut sets, minimal path sets, or binary decision diagrams (BDDs), and then, calculates top event probability and importance measures. This paper presents a new linear time algorithm to detect modules of large fault trees. It is shown through benchmark tests that the new method proposed in this study can very quickly detect the modules of a huge fault tree. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

• Journal of Korean Institute of Industrial Engineers
• /
• v.27 no.4
• /
• pp.379-383
• /
• 2001

The restricted shortest path problem is known to be weakly NP-hard and solvable in pseudo-polynomial time. Four fully polynomial approximation schemes (FPAS) are available in the literature, and most of these are based on pseudo-polynomial algorithms. In this paper, we propose a new FPAS that can be easily derived from a combination of a set of standard techniques. Although the complexity of the suggested algorithm is not as good as the fastest one available in the literature, it is practical in the sense that it does not rely on the bound tightening phase based on approximate binary search as in Hassin's fastest algorithm. In addition, we provide a review of standard techniques of existing works as a useful reference.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.285-289
• /
• 1992

This paper describes a new optimization technique for the design of traffic signal patterns. The proposed method uses a Genetic Algorithm for searching through the better signal patterns. Since the Genetic Algorithm is effective to search directly through a huge binary coded state spaces, the proposed design method has the following advantages over the conventional OR methods: (1) on-line optimization is available within a reasonable time, (2) there is no limitation to the types of signals to be optimized. Some computer simulations are carried out and its ability of getting high quality control in a short period is demonstrated.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.16 no.4
• /
• pp.520-527
• /
• 2016

A new dual-loop digital delay-locked loop (DLL) using a hybrid (binary + sequential) search algorithm is presented to achieve both wide-range operation and high delay resolution. A new phase-interpolation range selector (PIRS) and a variable successive approximation register (VSAR) algorithm are adopted to resolve the boundary switching and harmonic locking problems of conventional digital DLLs. The proposed digital DLL, implemented in a $0.18-{\mu}m$ CMOS process, occupies an active area of $0.19mm^2$ and operates over a wide frequency range of 0.15-1.5 GHz. The DLL dissipates a power of 11.3 mW from a 1.8 V supply at 1 GHz. The measured peak-to-peak output clock jitter is 24 ps (effective pk-pk jitter = 16.5 ps) with an input clock jitter of 7.5 ps at 1.5 GHz. The delay resolution is only 2.2 ps.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.12
• /
• pp.1891-1904
• /
• 2013

In RFID System, one of the problem that we must slove is to devise a good anti-collision algorithms to improve the efficiency of tag identification which is usually low because of tag collision. Among of the existing RFID anti-collision algorithm, BS (Binary Search) algorithm, though simple, has a disadvantage that the stage 0f times used to identify the tags increase exponentially as the number of tags does. In this Paper, I propose a new anti-collision algorithm called Multi-collision reflected frame which restricts the number of stages and decided bit. Since the proposal algorithm keep the length size of UID and density of total tag when have 100%.