• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• Structural Engineering and Mechanics
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• 제90권3호
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• pp.273-285
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• 2024

Tapered girders emerged as an economical remedy for the challenges associated with constructing long-span buildings. From an economic standpoint, these systems offer significant advantages, such as wide spans, quick assembly, and convenient access to utilities between the beam's shallow sections and the ceiling below. Elastic-local buckling is among the various failure modes that structural designers must account for during the design process. Despite decades of study, there remains a demand for efficient and comprehensive procedures to streamline product design. One of the most pressing requirements is a better understanding of the tapered web plate girder's local buckling behavior. This paper conducts a comprehensive numerical analysis to estimate the critical buckling coefficient for simply supported tapered steel web plates, considering loading conditions involving compression and bending stresses. An eigenvalue analysis was carried out to determine the natural frequencies and corresponding mode shapes of tapered web plates with varying geometric parameters. Additionally, the study highlights the relative significance of various parameters affecting the local buckling phenomenon, including the tapering ratio of the panel, normalized plate length, and ratio of minimum to maximum compressive stresses. The regression analysis and optimization techniques were performed using MATLAB software for the results of the finite element models to propose a separate formula for each load case and a unified formula covering different compression and bending cases of the elastic local buckling coefficient. The results indicate that the proposed formulas are applicable for estimating the critical buckling coefficient for simply supported tapered steel web plates.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.740-749
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• 1998

This paper proposes compression of image data using neural networks based on conjugate gradient method and dynamic tunneling system. The conjugate gradient method is applied for high speed optimization .The dynamic tunneling algorithms, which is the deterministic method with tunneling phenomenon, is applied for global optimization. Converging to the local minima by using the conjugate gradient method, the new initial point for escaping the local minima is estimated by dynamic tunneling system. The proposed method has been applied the image data compression of 12 ${\times}$12 pixels. The simulation results shows the proposed networks has better learning performance , in comparison with that using the conventional BP as learning algorithm.

• Journal of Welding and Joining
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• 제21권7호
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• pp.42-48
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• 2003

Welding distortion is a current issue in many industrial parts, especially for heavy industry such as shipbuilding, plant industry. The welding process has many processing parameters influencing welding angular distortion such as heat input power, welding speed, gas flow rate, plate thickness and the welded material properties, etc. In this work, the conventional local minimization concept was applied to find a set of optimum welding process parameters, consisted of welding speed, plate thickness and heat input, for a minimum angular distortion. An analytic solution for welding angular distortion, which is based on laminated plate theory, was also applied to investigate and optimize the welding process parameters. The optimized process parameters and the angular distortion for various parametric conditions could be easily found by using the local minimum concept.

• 대한산업공학회지
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• 제28권1호
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• pp.76-86
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• 2002

In this paper, we suggest a hybrid genetic algorithm reinforced by a fuzzy logic controller (flc-HGA) to overcome weaknesses of conventional genetic algorithms: the problem of parameter fine-tuning, the lack of local search ability, and the convergence speed in searching process. In the proposed flc-HGA, a fuzzy logic controller is used to adaptively regulate the fine-tuning structure of genetic algorithm (GA) parameters and a local search technique is applied to find a better solution in GA loop. In numerical examples, we apply the proposed algorithm to a simple test problem and two complex combinatorial optimization problems. Experiment results show that the proposed algorithm outperforms conventional GAs and heuristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1086-1091
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• 2005

This paper focuses on intelligent control of induction motor by hybrid system consisting of GA-PSO. Induction motor has been using in industrial area. However, it is challengeable on how we control effectively. From this point, an optimal solution using GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is introduced to intelligent control. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent. To improve an optimal learning solution of control, This paper deal with applying PSO and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.21-28
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• 2005

This paper proposes a new method for accelerating the search speed of genetic algorithms by taking derivative evaluation and conditional random selection into account in their evolution process. Derivative evaluation makes genetic algorithms focus on the individuals whose fitness is rapidly increased. This accelerates the search speed of genetic algorithms by enhancing exploitation like steepest descent methods but also increases the possibility of a premature convergence that means most individuals after a few generations approach to local optima. On the other hand, derivative evaluation under a premature convergence helps genetic algorithms escape the local optima by enhancing exploration. If GAs fall into a premature convergence, random selection is used in order to help escaping local optimum, but its effects are not large. We experimented our method with one combinatorial problem and five complex function optimization problems. Experimental results showed that our method was superior to the simple genetic algorithm especially when the search space is large.

• 한국군사과학기술학회지
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• 제13권2호
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• pp.171-179
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• 2010

A fundamental technology of UGV(Unmanned Ground Vehicle) to perform a given mission with success in various environment is a path planning method which generates a safe and optimal path to the goal. In this paper, we suggest a local path-planning method of UGV based on the binary map using world model data which is gathered from terrain perception sensors. In specially, we present three core algorithms such as shortest path computation algorithm, path optimization algorithm and path smoothing algorithm those are used in the each composition module of LPP component. A simulation is conducted with M&S(Modeling & Simulation) system in order to verify the performance of each core algorithm and the performance of LPP component with scenarios.

• 산업공학
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• 제8권1호
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• pp.23-30
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• 1995

Optimization in the engineering design is to select the best of many possible design alternatives in a complex design space. One major problem of local minimization algorithm is that they often result in local optima. In this paper, a hybrid method was developed by coupling the genetic algorithm and a traditional direct search method. The proposed method first finds a region for possible global optimum using the genetic algorithm and then searchs for a global optimum using the direct search method. To evaluate the performance of the hybrid method, it was applied to three test problems and a problem of designing corrugate bulkhead of a ship.

• 대한수학회지
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• 제48권5호
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• pp.985-999
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• 2011

A new filled function method is presented in this paper to solve box-constrained nonlinear integer programming problems. It is shown that for a given non-global local minimizer, a better local minimizer can be obtained by local search starting from an improved initial point which is obtained by locally solving a box-constrained integer programming problem. Several illustrative numerical examples are reported to show the efficiency of the present method.