• Title/Summary/Keyword: gradient algorithm

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A Design and Implement of Efficient Agricultural Product Price Prediction Model

  • Im, Jung-Ju;Kim, Tae-Wan;Lim, Ji-Seoup;Kim, Jun-Ho;Yoo, Tae-Yong;Lee, Won Joo
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.5
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    • pp.29-36
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    • 2022
  • In this paper, we propose an efficient agricultural products price prediction model based on dataset which provided in DACON. This model is XGBoost and CatBoost, and as an algorithm of the Gradient Boosting series, the average accuracy and execution time are superior to the existing Logistic Regression and Random Forest. Based on these advantages, we design a machine learning model that predicts prices 1 week, 2 weeks, and 4 weeks from the previous prices of agricultural products. The XGBoost model can derive the best performance by adjusting hyperparameters using the XGBoost Regressor library, which is a regression model. The implemented model is verified using the API provided by DACON, and performance evaluation is performed for each model. Because XGBoost conducts its own overfitting regulation, it derives excellent performance despite a small dataset, but it was found that the performance was lower than LGBM in terms of temporal performance such as learning time and prediction time.

Automatic Pedestrian Removal Algorithm Using Multiple Frames (다중 프레임에서의 보행자 검출 및 삭제 알고리즘)

  • Kim, ChangSeong;Lee, DongSuk;Park, Dong Sun
    • Smart Media Journal
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    • v.4 no.2
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    • pp.26-33
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    • 2015
  • In this paper, we propose an efficient automatic pedestrian removal system from a frame in a video sequence. It firstly finds pedestrians from the frame using a Histogram of Oriented Gradient(HOG) / Linear-Support Vector Machine(L-SVM) classifier, searches for proper background patches, and then the patches are used to replace the deleted pedestrians. Background patches are retrieved from the reference video sequence and a modified feather blender algorithm is applied to make boundaries of replaced blocks look naturally. The proposed system, is designed to automatically detect object and generate natural-looking patches, while most existing systems provide search operation in manual. In the experiment, the average PSNR of the replaced blocks is 19.246

Pseudo-Distance Map Based Watersheds for Robust Region Segmentation

  • Jeon, Byoung-Ki;Jang, Jeong-Hun;Hong, Ki-Sang
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.283-286
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    • 2001
  • In this paper, we present a robust region segmentation method based on the watershed transformation of a pseudo-distance map (PDM). A usual approach for the segmentation of a gray-scale image with the watershed algorithm is to apply it to a gradient magnitude image or the Euclidean distance map (EDM) of an edge image. However, it is well known that this approach suffers from the oversegmentation of the given image due to noisy gradients or spurious edges caused by a thresholding operation. In this paper we show thor applying the watershed algorithm to the EDM, which is a regularized version of the EDM and is directly computed form the edgestrength function (ESF) of the input image, significantly reduces the oversegmentation, and the final segmentation results obtained by a simple region-merging process are more reliable and less noisy than those of the gradient-or EDM-based methods. We also propose a simple and efficient region-merging criterion considering both boundary strengths and inner intensities of regions to be merged. The robustness of our method is proven by testing it with a variety of synthetic and real images.

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Selecting Fuzzy Rules for Pattern Classification Systems

  • Lee, Sang-Bum;Lee, Sung-joo;Lee, Mai-Rey
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.2
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    • pp.159-165
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    • 2002
  • This paper proposes a GA and Gradient Descent Method-based method for choosing an appropriate set of fuzzy rules for classification problems. The aim of the proposed method is to fond a minimum set of fuzzy rules that can correctly classify all training patterns. The number of inference rules and the shapes of the membership functions in the antecedent part of the fuzzy rules are determined by the genetic algorithms. The real numbers in the consequent parts of the fuzzy rules are obtained through the use of the descent method. A fitness function is used to maximize the number of correctly classified patterns, and to minimize the number of fuzzy rules. A solution obtained by the genetic algorithm is a set of fuzzy rules, and its fitness is determined by the two objectives, in a combinatorial optimization problem. In order to demonstrate the effectiveness of the proposed method, computer simulation results are shown.

AN EFFICIENT ALGORITHM FOR INCOMPRESSIBLE FREE SURFACE FLOW ON CARTESIAN MESHES (직교격자상에서 효율적인 비압축성 자유표면유동 해법)

  • Go, G.S.;Ahn, H.T.
    • Journal of computational fluids engineering
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    • v.19 no.4
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    • pp.20-28
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    • 2014
  • An efficient solution algorithm for simulating free surface problem is presented. Navier-Stokes equations for variable density incompressible flow are employed as the governing equation on Cartesian meshes. In order to describe the free surface motion efficiently, VOF(Volume Of Fluid) method utilizing THINC(Tangent of Hyperbola for Interface Capturing) scheme is employed. The most time-consuming part of the current free surface flow simulations is the solution step of the linear system, derived by the pressure Poisson equation. To solve a pressure Poisson equation efficiently, the PCG(Preconditioned Conjugate Gradient) method is utilized. This study showed that the proper application of the preconditioner is the key for the efficient solution of the free surface flow when its pressure Poisson equation is solved by the CG method. To demonstrate the efficiency of the current approach, we compared the convergence histories of different algorithms for solving the pressure Poisson equation.

Cost optimization of reinforced high strength concrete T-sections in flexure

  • Tiliouine, B.;Fedghouche, F.
    • Structural Engineering and Mechanics
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    • v.49 no.1
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    • pp.65-80
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    • 2014
  • This paper reports on the development of a minimum cost design model and its application for obtaining economic designs for reinforced High Strength Concrete (HSC) T-sections in bending under ultimate limit state conditions. Cost objective functions, behavior constraint including material nonlinearities of steel and HSC, conditions on strain compatibility in steel and concrete and geometric design variable constraints are derived and implemented within the Conjugate Gradient optimization algorithm. Particular attention is paid to problem formulation, solution behavior and economic considerations. A typical example problem is considered to illustrate the applicability of the minimum cost design model and solution methodology. Results are confronted to design solutions derived from conventional design office methods to evaluate the performance of the cost model and its sensitivity to a wide range of unit cost ratios of construction materials and various classes of HSC described in Eurocode2. It is shown, among others that optimal solutions achieved using the present approach can lead to substantial savings in the amount of construction materials to be used. In addition, the proposed approach is practically simple, reliable and computationally effective compared to standard design procedures used in current engineering practice.

Contents-based digital still-image protection using OCL (OCL을 이용한 콘텐츠 기반의 정지영상 보호 기법 연구)

  • Yoo, Hyouck-Min;Shin, Jin-Wook;Park, Dong-Sun;Yoon, Sook
    • Korean Journal of Cognitive Science
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    • v.21 no.1
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    • pp.145-156
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    • 2010
  • This paper presents a new contents-based digital still image protection method which includes a copyright message. Since the existing method using gradient values used a pixel based $3{\times}3$ Sobel operator, it was sensitive to attacks and could not extract exact copyright message. Therefore, in this paper, we present a algorithm which uses block based OCL(Orientation Certainty Level) instead of pixel. The experimental results show that the proposed scheme not only has good image quality, but also is robust to JPEG lossy compression, filtering, sharpening, blurring and noise. Moreover, the proposed algorithm has good performance more than 10% in rotation attacks than the existing method.

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The Response Improvement of PD Type FLC System by Self Tuning (자기동조에 의한 PD 형 퍼지제어시스템의 응답 개선)

  • Choi, Hansoo;Lee, Kyoung-Woong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.12
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    • pp.1101-1105
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    • 2012
  • This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

Design & Implementation of Pedestrian Detection System Using HOG-PCA Based pRBFNNs Pattern Classifier (HOG-PCA기반 pRBFNNs 패턴분류기를 이용한 보행자 검출 시스템의 설계 및 구현)

  • Kim, Jin-Yul;Park, Chan-Jun;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.7
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    • pp.1064-1073
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    • 2015
  • In this study, we introduce the pedestrian detection system by using the feature of HOG-PCA and RBFNNs pattern classifier. HOG(Histogram of Oriented Gradient) feature is extracted from input image to identify and recognize a object. And a dimension is reduced for improving performance as well as processing speed by using PCA which is a typical dimensional reduction algorithm. So, the feature of HOG-PCA through the dimensional reduction by using PCA leads to the improvement of the detection rate. FCM clustering algorithm is used instead of gaussian function to apply the characteristic of input data as well and connection weight is used by polynomial expression such as constant, linear, quadratic and modified quadratic. Finally, INRIA person database known as one of the benchmark dataset used for pedestrian detection is applied for the performance evaluation of the proposed classifier. The experimental result of the proposed classifier are compared with those studied by Dalal.

Comparison of Gradient Calculation Methods for Directivity Optimization of Adaptive Ultrasonic Transducers (적응형 초음파 트랜스듀서의 지향성 최적화를 위한 구배계산법의 비교)

  • ;Takao Tsuchiya;Yukio Kagawa
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.5
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    • pp.61-68
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    • 2001
  • In this paper, an analytical method and a difference approximation method to calculate the gradient of an objective function have been applied to the directivity optimization in an adaptive ultrasonic transducer which is combined with a point source array and an optimization algorithm (DFP method). To compare these two methods, quasi-ideal .beam with a beam width and direction specified are chosen as the desired directivity. As the numerical results, the difference approximation method shows better suppressive capacity of side lobe level, good stability in the convergence processing, faster convergence speed and excellent adaptability compared with the analytical method.

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