• The Journal of the Korea institute of electronic communication sciences
• /
• v.7 no.4
• /
• pp.789-796
• /
• 2012

To find the module sequence that makes correction rate optimal is the goal of this paper. The Hill-climbing algorithm was used in the experiment to analyze the performance of Korean Spelling Corrector. Given the wrong eojul set, We found the module sequence that shows correction rate of 96.41%. Because of the quite high correction rate, Hill-climbing is a practical method for our Spelling Corrector.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.1 s.39
• /
• pp.129-138
• /
• 2006

Various techniques have been applied to solve the maximal covering problem. Tabu search is also one of them. But, existing researches were lacking of the synthetic analysis and the effort for performance improvement about neighborhood search techniques such as hill-climbing search and simulated annealing including tabu search. In this paper, I introduce the way to improve performance of neighborhood search techniques through various experiments and analyses. Basically, all neighborhood search algorithms use the k-exchange neighborhood generation method. And I analyzed how the performance of each algorithm changes according to various parameter settings. Experimental results have shown that simple hill-climbing search and simulated annealing can produce better results than any other techniques. And I confirmed that simple hill-climbing search can produce similar results as simulated annealing unlike general case.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.9 no.3
• /
• pp.257-265
• /
• 2016

In this study, an optimal design for motor-driven track type traveling system applied into high clearance working machineries in orchard is proposed. Tractive performance and hill climbing ability were predicted and evaluated for the optimal motor traveling system by taking into account of soil characteristics in orchard utilizing the high clearance working machineries. Design criteria for tractive performance were based on the traction force calculated from tractive effort subtracted by motion resistance, while hill climbing ability had its design criteria that fulfill the climbing 20% slope ground at a speed of 3km/h. Based on the evaluation results of traction and climbing ability, two DC48V, 4500rpm, 1.6kW AC motors were independently applied to both left and right side of orbits; each motor is designed to transmit power on driving sprocket of track type traveling system via 50:1 reduction gear ratio. The motor-driven track type traveling system developed in the study found to have 396 kgf of tractive force, which is 12.5% higher than climbing resistance at orchard soil having 20% slope ground (352 kgf), demonstrating sufficient tractive performance and hill climbing ability.

• Journal of Astronomy and Space Sciences
• /
• v.31 no.4
• /
• pp.347-351
• /
• 2014

Planetary exploration rovers are likely to make a trip on a winding and sloping road of irregular surfaces to the destination in order to accomplish scientific missions. One of the key technologies for rovers is a suspension for traveling and performing exploration missions; the suspension is an essential area of technology for a stable movement of a rover. In this study, an 8-wheel suspension is designed to enable efficient climbing of slopes on a passage to the destination. For the two front wheels among the eight wheels, the moment at the pivot connecting two wheels is derived when the distance between the wheels and the torque of wheels are same. A test experiment was performed to compare the magnitude of moment according to the change in tilt angle and the position of the pivot. Finally, a suspension design considering the position of the pivot was proposed to enhance the hill-climbing performance.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.22 no.4
• /
• pp.467-474
• /
• 2019

Recently, optical phased array(OPA) based laser detection and ranging(LADAR) has gained great interest to replace the traditional mechanical light detection and ranging technique(LiDAR). In OPA-based LADAR, it is well known that phases of laser pulses traveling through each of channels should be the same to obtain a narrow free-space single beam without noise-like ripples in the far field. However, it is difficult to provide such ideal condition due to the fabrication errors. To tackle this problem, any algorithms should be necessary to compensate the initial random phases of each channel in OPA antenna. In this paper, we propose a hill-climbing based phase calibration algorithm and evaluate the performance of the proposed algorithm.

• Journal of information and communication convergence engineering
• /
• v.16 no.4
• /
• pp.264-270
• /
• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.4
• /
• pp.1523-1531
• /
• 2011

Multi-axle driving vehicle are favored for military use in off road operations because of their high mobility on extreme terrains and obstacles. Especially, Military Vehicle needs an ability to driving on hills of 60% angle slope. This paper presents the improvement of the ability of hill climbing for 6WD/6WS vehicle through the optimal tire force distribution method. From the driver's commands, the desired longitudinal force, the desired lateral force, and the desired yaw moment were obtained for the hill climbing of vehicle using optimal tire force distribution method. These three values were distributed to each wheel as the torque based on optimal tire force distribution method using friction circle and cost function. To verify the performance of the proposed algorithm, the simulation is executed using TruckSim software. Two vehicles, the one the proposed algorithm is implemented and the another the tire's forces are equivalently distributed, are compared. At the hill slop, the ability to driving on hills is improved by using the optimum tire force distribution method.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.111-113
• /
• 2006

DEAS is an direct searching and optimization method that based on the binary code space. It can be classified as an direct hill climbing searching. However, because of binary code space based searching, the searching in low resolution has random property. As the resolution of code increases during the search, its property of searching changes like that of hill climbing search. This paper propose a method for improving the performance of minimum seeking ability of DEAS with history information. The cost evaluation is increased. However the minimum searching ability of DEAS is improved along the same starting resolution.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.10
• /
• pp.819-826
• /
• 2001

Genetic algorithms are becoming more popular because of their relative simplicity and robustness. Genetic algorithms are global search techniques for nonlinear optimization. However, traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain because they are poor at hill-climbing, whereas simulated annealing has the ability of probabilistic hill-climbing. Therefore, hybridizing a genetic algorithm with other algorithms can produce better performance than using the genetic algorithm or other algorithms independently. In this paper, we propose an efficient hybrid optimization algorithm named the adaptive random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural networks. This paper describes the application of genetic algorithms and simulated annealing to a random signal-based learning in order to generate the parameters and reinforcement signal of the random signal-based learning, respectively. The validity of the proposed algorithm is confirmed by applying it to two different examples.

• Journal of Multimedia Information System
• /
• v.2 no.1
• /
• pp.179-186
• /
• 2015

This paper describes the application of a simulated annealing to a random signal-based learning. The simulated annealing is used to generate the reinforcement signal which is used in the random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural network. It is poor at hill-climbing, whereas simulated annealing has an ability of probabilistic hill-climbing. Therefore, hybridizing a random signal-based learning with the simulated annealing can produce better performance than before. The validity of the proposed algorithm is confirmed by applying it to two different examples. One is finding the minimum of the nonlinear function. And the other is the optimization of fuzzy control rules using inverted pendulum.