• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.257-266
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• 2015

There is no polynomial-time algorithm that can be obtain the optimal solution for economic load dispatch problem with non-convex fuel cost functions. Therefore, electrical field uses quadratic fuel cost function unavoidably. This paper proposes a valve-point optimization (VPO) algorithm for economic load dispatch problem with non-convex fuel cost functions. This algorithm sets the initial values to maximum powers $P_i{\leftarrow}P_i^{max}$ for each generator. It then reduces the generation power of generator i with an average power cost of $_{max}\bar{c}_i$ to a valve point power $P_{ik}$. The proposed algorithm has been found to perform better than the extant heuristic methods when applied to 13 and 40-generator benchmark data. This paper consequently proves that the optimal solution to economic load dispatch problem with non-convex fuel cost functions converges to the valve-point power of each generator.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.171-176
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• 2020

This paper proposes polynomial-time algorithm for maximum weighted independent set(MWIS) problem that is well known as NP-hard. The known algorithms for MWIS problem are polynomial-time to specialized in particular graph type, distributed, or clustering method. But there is no unified algorithm is suitable to all kinds of graph types. Therefore, this paper suggests unique polynomial-time algorithm that is suitable to all kinds of graph types. The proposed algorithm merges the maximum weighted vertex v_i and maximum weighted vertex v_j that is not adjacent to v_i. As a result of apply to undirected graphs and trees, this algorithm can be get the optimal solution. This algorithm improves previously known solution to new optimal solution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.115-123
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• 2011

Distribution system loss minimization re-configuration is 0-1 planning problem, and the number of combinations requiring searches is extremely large when dealing with typical system scales. For this reason, the application of a genetic algorithm (GA) seems a tractive to solve this problem. Although Genetic algorithms are a type of random number search method, they incorporate a multi-point search feature and are therefore superior to one-point search techniques. The incorporate of GAs for solving large combinational problem has received wide attention. Further, parallel searching can be performed and the optimal solution is more easily reach ed. In this paper, for improving GA convergence characteristics in the distribution system loss minimization re-configuration problem, a chromosome "Limited Life" concept is introduced. Briefly, considering the population homogenization and genetic drift problems, natural selection is achieved by providing this new concept, in addition to natural selection by fitness. This is possible because individuals in a population have an age value. Simulation were carried out using a model system to check this method's validity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.141-147
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• 2021

In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.95-102
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• 2022

This paper proposed a linear time algorithm for a three-partition problem(TPP) in which a polynomial time algorithm is not known as NP-complete. This paper proposes a backtracking method that improves the problems of not being able to obtain a solution of the MM method using the sum of max-min values and third numbers, which are known polynomial algorithms in the past. In addition, the problem of MM applying the backtracking method was improved. The proposed algorithm partition the descending ordered set S into three and assigned to the forward, backward, and best-fit allocation method with maximum margin, and found an optimal solution for 50.00%, which is 5 out of 10 data in initial allocation phase. The remaining five data also showed performance to find the optimal solution by exchanging numbers between surplus boxes and shortage boxes at least once and up to seven times. The proposed algorithm that performs simple allocation and exchange optimization with less O(k) linear time performance complexity than the three-partition m=n/3 data, and it was shown that there could be a polynomial time algorithm in which TPP is a P-problem, not NP-complete.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.185-191
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• 2023

To the exact cover problem that remains NP-complete to which no polynomial time algorithm is made available, this paper proposes a linear time algorithm that yields an optimal solution. The proposed algorithm makes use of the set cover problem's major feature which states that "no identical element shall be included in more than one covering set". To satisfy this criterion, the proposed algorithm initially selects a subset with the minimum cardinality and deletes those that contain the cardinality identical to that of the selected subset. This process is repeatedly performed on remaining subsets until the final solution is obtained. Provided that the solution is unattainable, it selects subsets with the maximum cardinality and repeats the same process. The proposed algorithm has not only obtained the optimal solution with ease but also proved its wide applicability on N-queens problems, hence disproving the NP-completeness of the exact cover problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.165-170
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• 2023

This paper proposes an algorithm that can obtain a solution with linear time for a set cover problem(SCP) in which there is no polynomial time algorithm as an NP-complete problem so far. Until now, only heuristic greed algorithms are known to select sets that can be covered to the maximum. On the other hand, the proposed algorithm is a competitive algorithm that applies an inclusion-exclusion principle rule to N nodes up to 2nd or 3rd in the maximum number of elements to obtain a set covering all k nodes, and selects the minimum cover set among them. The proposed algorithm compensated for the disadvantage that the greedy algorithm does not obtain the optimal solution. As a result of applying the proposed algorithm to various application cases, an optimal solution was obtained with a polynomial time of O(kn²).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.33-39
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• 2023

Recently, reinforcement learning has been used to improve the communication performance of flying ad-hoc networks (FANETs) and to design mobility models. Mobility model is a key factor for predicting and controlling the movement of unmmaned aerial vehicle (UAVs). In this paper, we designed and analyzed the performance of Q-learning with fourier basis function approximation and Deep-Q Network (DQN) models for optimal path finding in a three-dimensional virtual environment where UAVs operate. The experimental results show that the DQN model is more suitable for optimal path finding than the Q-learning model in a three-dimensional virtual environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.31-37
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• 2009

In the two-way relay channel, the relay employ Amplify-and-Forward (AF) or Decode-and-Forward (DF) protocol, and broadcast the network-coded signal to both user. In the system, DF protocol provides maximum throughput at low signal to noise ratio(SNR). On the other hand, at high SNR, AF protocol provides maximum throughput. The paper propose active transmission scheme which employ Amplify-and-Forward or Decode-and-Forward protocol based on received SNR at the relay over Two-way relay channel. The optimal threshold is investigated numerically for switching the protocol. Through numerical results, we confirm that the proposed scheme outperforms conventional schemes over two-way relay channel.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.226-231
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• 2020

In order to maximize the production of landscape plants in optimal condition while coexisting with the environment in terms of precision agriculture, quick and accurate information gathering of the internal environmental elements of the growing container is necessary. This may depend on the accuracy of the positioning of numerous sensors connected to landscape plants cultivating system (LPCS) in containers. Thus, this paper presents a method for estimating the location of the sensors related to cultivation environment connected to LPCS by measuring the received signal strength (RSS) or time of arrival TOA received between oneself and adjacent sensors. The Small sensors connected to the LPCS of container are known for their locations, but the remaining locations must be estimated. For this in the paper, Rao-Cramer limits and maximum likelihood estimators are derived from Gaussian models and lognormal models for TOA and RSS measurements, respectively. As a result, this study suggests that both RSS and TOA range measurements can produce estimates of the exact locations of the cultivation environment sensors within the wireless sensor network related to the LPCS.