• Advances in Computational Design
• /
• v.4 no.3
• /
• pp.197-210
• /
• 2019

Motion generation of a four-bar linkage is a type of mechanism synthesis that has a wide range of applications such as a pick-and-place operation in manufacturing. In this research, the use of meta-heuristics for motion generation of a four-bar linkage is demonstrated. Three problems of motion generation were posed as a constrained optimization probably using the weighted sum technique to handle two types of tracking errors. A simple penalty function technique was used to deal with design constraints while three meta-heuristics including differential evolution (DE), self-adaptive differential evolution (JADE) and teaching learning based optimization (TLBO) were employed to solve the problems. Comparative results and the effect of the constraint handling technique are illustrated and discussed.

• International Journal of Computer Science & Network Security
• /
• v.24 no.10
• /
• pp.109-114
• /
• 2024

Wireless Sensor Networks (WSN) includes a large number of small sensor nodes and low cost, which are randomly located in a region. The wireless sensor network has attracted much attention from universities and industry around the world over the past decades, with features denser levels of node deployment, self-configuration, uncertainty of sensor nodes, computing, and memory constraints. Black-hole attack is one of the most known attacks on this network. In this study, the combination of fuzzy logic and particle swarm optimization (PSO) algorithms is proposed as an effective method for detecting black-hole attack in the AODV protocol. In the current study, a new function has been proposed in order to determine the membership of fuzzy parameters based on the particle swarm optimization algorithm. The proposed method was evaluated in different scenarios and was compared with other state of arts. The simulation result of this method proved the better performance in both detection rate and delivered packet rate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.11
• /
• pp.2824-2838
• /
• 2013

There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.8
• /
• pp.3841-3861
• /
• 2017

Virtualized small cell network is a promising architecture which can realize efficient utilization of the network resource. However, conventional full duplex self-backhauls lead to residual self-interference, which limits the network performance. To handle this issue, this paper proposes a virtual resource allocation, in which the residual self-interference is fully exploited by employing a physical-layer network coding (PNC) aided self-backhaul scheme. We formulate the features of PNC as time slot and information rate constraints, and based on that, the virtual resource allocation is formulated as a mixed combinatorial optimization problem. To solve the problem efficiently, it is decomposed into two sub problems, and a two-phase iteration algorithm is developed accordingly. In the algorithm, the first sub problem is approximated and transferred into a convex problem by utilizing the upper bound of the PNC rate constraint. On the basis of that, the convexity of the second sub problem is also proved. Simulation results show the advantages of the proposed scheme over conventional solution in both the profits of self-backhauls and utility of the network resource.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38B no.1
• /
• pp.18-25
• /
• 2013

In this paper, we propose a self-optimization scheme for indoor femtocell coverage in heterogeneous networks. If the femtocell coverage is larger than indoor area, neighbor cell users passing by the outer area of the femtocell coverage may request an unnecessary handover which incurs wasteful signaling overhead. On the other hand, if the coverage is smaller than the indoor area, some of indoor users might not be connected to the indoor femtocell. Therefore, we propose the method by which the femtocell coverage attains the exact indoor area employing self-organized scheme. Autonomous self TX power adjustment of the femtocell is possible because the proposed method utilizes handover request events and membership information of users that can be obtained by the femtocell itself. We show that the TX power obtained by the proposed algorithm converges to the optimal TX power that can be obtained analytically to attain the indoor coverage area.

• Nuclear Engineering and Technology
• /
• v.55 no.9
• /
• pp.3150-3163
• /
• 2023

To improve the performance of blanket: maximizing the tritium breeding rate (TBR) for tritium self-sufficiency, and minimizing the Dose of backplate for radiation protection, most previous studies are based on manual corrections to adjust the blanket structure to achieve optimization design, but it is difficult to find an optimal structure and tends to be trapped by local optimizations as it involves multiphysics field design, which is also inefficient and time-consuming process. The artificial intelligence (AI) maybe is a potential method for the optimization design of the blanket. So, this paper aims to develop an intelligent optimization method based on an improved multi-objective NSGA-III algorithm and an adaptive BP neural network to solve these problems mentioned above. This method has been applied on optimizing the radial arrangement of a conceptual design of CFETR HCSB blanket. Finally, a series of optimal radial arrangements are obtained under the constraints that the temperature of each component of the blanket does not exceed the limit and the radial length remains unchanged, the efficiency of the blanket optimization design is significantly improved. This study will provide a clue and inspiration for the application of artificial intelligence technology in the optimization design of blanket.

• Structural Engineering and Mechanics
• /
• v.84 no.4
• /
• pp.489-502
• /
• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.1
• /
• pp.88-93
• /
• 2008

The electromagnetic parameters of a permanent magnet synchronous motor (PMSM) such as the open load permanent magnet flux, d axis reactance $X_d$, and q axis reactance $X_q$, are most essential to the performance analysis and optimization design of the motor. Based on the numerical analysis of the 3D electromagnetic field, the three electromagnetic parameters of permanent magnet synchronous motors with U form interior rotor structures are calculated by FEA. The rules of the leakage coefficient and reactance parameters changing with the air gap length, permanent magnet magnetism length, and isolation magnetic bridge dimensions in the rotor are given. The calculated values agree well with the measured values. The FEA results are integrated with the self compiled electromagnetic design program to optimize the prototype motor. The tested performances of the prototype motor prove that the method is suitable for the optimization of motor structure.

• Smart Media Journal
• /
• v.13 no.2
• /
• pp.129-135
• /
• 2024

In this paper, we propose a new approach that enhances the continuous optimization performance of the MAP-Elites algorithm. The existing self-referencing MAP-Elites algorithm employed the "DE/rand/1/bin" operator from the differential evolution algorithm, which, due to its lack of rotational invariance, led to a degradation in optimization performance when there were high correlations among variables. The proposed algorithm replaces the "DE/rand/1/bin" operator with the "DE/current-to-rand/1" operator. This operator, possessing rotational invariance, ensures robust performance even in cases where there are high correlations among variables. Experimental results confirm that the proposed algorithm performs better than the comparison algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.3
• /
• pp.205-223
• /
• 2010

In this paper, we analyze the impact of different frame types on self-similarity and burstiness characteristics of the aggregated frame traffic from a real 802.11 wireless local area network. We find that characteristics of aggregated frame traffic are affected by both mean frame size and the proportion of specified frame types. Based on this new knowledge, an adaptative frame size optimization (AFSO) mechanism is proposed to improve the transmission efficiency by adaptively adjusting data frame size according to the proportions of different frame types. Simulation results show that our proposed mechanism can effectively regulate the burstiness of aggregated frame traffic and improve the successful delivery rate of data frames when a fixed throughput target is set for 802.11 wireless networks.