• Title/Summary/Keyword: Artificial Distribution

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Artificial Intelligence Application using Nutcracker Optimization Algorithm to Enhance Efficiency & Reliability of Power Systems via Optimal Setting and Sizing of Renewable Energy Sources as Distributed Generations in Radial Distribution Systems

  • Nawaf A. AlZahrani;Mohammad Hamza Awedh;Ali M. Rushdi
    • International Journal of Computer Science & Network Security
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    • v.24 no.1
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    • pp.31-44
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    • 2024
  • People have been using more energy in the last years. Several research studies were conducted to develop sustainable energy sources that can produce clean energy to fulfill our energy requirements. Using renewable energy sources helps to decrease the harm to the environment caused by conventional power plants. Choosing the right location and capacity for DG-RESs can greatly impact the performance of Radial Distribution Systems. It is beneficial to have a good and stable electrical power supply with low energy waste and high effectiveness because it improves the performance and reliability of the system. This research investigates the ideal location and size for solar and wind power systems, which are popular methods for producing clean electricity. A new artificial intelligent algorithm called Nutcracker Optimization Algorithm (NOA) is used to find the best solution in two common electrical systems named IEEE 33 and 69 bus systems to examine the improvement in the efficiency & reliability of power system network by reducing power losses, making voltage deviation smaller, and improving voltage stability. Finally, the NOA method is compared with another method called PSO and developed Hybrid Algorithm (NOA+PSO) to validate the proposed algorithm effectiveness and enhancement of both efficiency and reliability aspects.

Advanced Big Data Analysis, Artificial Intelligence & Communication Systems

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.1-6
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    • 2019
  • Recently, big data and artificial intelligence (AI) based on communication systems have become one of the hottest issues in the technology sector, and methods of analyzing big data using AI approaches are now considered essential. This paper presents diverse paradigms to subjects which deal with diverse research areas, such as image segmentation, fingerprint matching, human tracking techniques, malware distribution networks, methods of intrusion detection, digital image watermarking, wireless sensor networks, probabilistic neural networks, query processing of encrypted data, the semantic web, decision-making, software engineering, and so on.

Analytical Study on Durability due to the Load of Artificial Knee Joint (무릎인공관절의 하중에 따른 내구성에 관한 해석적 연구)

  • Cho, Jae-Ung
    • Journal of the Korea Convergence Society
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    • v.5 no.2
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    • pp.7-11
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    • 2014
  • The artificial joint is consisted with the upper structure of tungsten alloy steel and the lower part of polyethelene are applied with load. When this joint is applied with load in this study, the load distribution at the joint and the stress distribution of support hole to install the joint are investigated by finite element analysis. These results can be utilized at obtaining the basic material to have the experiment for the real thing. The crack is initiated as the load is concentrated at the end of corner on the upper structure. This behavior is in accord with a case of tissue damage due to the breakage of artificial joint reported at medical science.

Effect of Shell Structure of Artificial Lightweight Aggregates on the Emission Rate of Absorbed Water (인공경량골재의 표피층 구조가 흡수된 물의 방출속도에 미치는 영향)

  • Kang, Seung-Gu
    • Journal of the Korean Ceramic Society
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    • v.45 no.11
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    • pp.750-754
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    • 2008
  • The artificial aggregates with dense surface layer (shell) was fabricated and the dependence of water emission rate upon the shell structures was studied. The EAF dust containing many flux components and waste white clay with ignition loss of above 48% were used as for liquid phase and gas forming agents during a sintering process respectively. In addition, the shell structure was modified with various processes and the modification effect on water emission rate was analyzed. The pores under $10{\mu}m$ were found in the sintered artificial light aggregates and disappeared by incorporating to a bigger pore during re-sintering. The water emission rate in an initial step depended on a void content of aggregates filled in a bottle rather than a shell structure. But, after 7 days where the water emission of the aggregate with a shell is above 40%, the shell of aggregates suppressed the water emission. The core of aggregates was exposed and most shell was lost when crushed to smaller size so, the ability for suppressing water emission of the crushed aggregates decreased. The activation energy for the water emission was $3.46{\pm}0.25{\times}10^{-1}$J/mol for the most specimens showing that the activation energy is irrelevant to the pore size distribution and shell structure.

Optimal placement of elastic steel diagonal braces using artificial bee colony algorithm

  • Aydin, E.;Sonmez, M.;Karabork, T.
    • Steel and Composite Structures
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    • v.19 no.2
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    • pp.349-368
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    • 2015
  • This paper presents a new algorithm to find the optimal distribution of steel diagonal braces (SDB) using artificial bee colony optimization technique. The four different objective functions are employed based on the transfer function amplitude of; the top displacement, the top absolute acceleration, the base shear and the base moment. The stiffness parameter of SDB at each floor level is taken into account as design variables and the sum of the stiffness parameter of the SDB is accepted as an active constraint. An optimization algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed to minimize the objective functions. The proposed ABC algorithm is applied to determine the optimal SDB distribution for planar buildings in order to rehabilitate existing planar steel buildings or to design new steel buildings. Three planar building models are chosen as numerical examples to demonstrate the validity of the proposed method. The optimal SDB designs are compared with a uniform SDB design that uniformly distributes the total stiffness across the structure. The results of the analysis clearly show that each optimal SDB placement, which is determined based on different performance objectives, performs well for its own design aim.

Dispersion-Managed Links for WDM Transmission Arranged by Linearly or Nonlinearly Incremented Residual Dispersion per Span

  • Lee, Seong-Real
    • Journal of information and communication convergence engineering
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    • v.15 no.4
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    • pp.205-211
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    • 2017
  • Combining dispersion-managed optical links with midway optical phase conjugation (OPC) is a possible method of compensating for optical signal distortion due to group velocity dispersion and nonlinear Kerr effects. Although an improvement in the performance of these optical links has been reported, the fixed residual dispersion per span (RDPS) that is typically used restricts the flexibility of link configurations. Thus, in this paper, a flexible dispersion-managed link configuration, comprising artificial distributions of linearly/nonlinearly incremented RDPS, is proposed. Simulations show that a descending distribution of RDPS before the midway OPC, and an ascending distribution of RDPS after the midway OPC, gives the best artificial distribution pattern as the number of fiber spans is increased, regardless of the RDPS incrementation method.

Estimating spatial distribution of water quality in landfill site

  • Yoon Hee-Sung;Lee Kang-Kun;Lee Seong-Soon;Lee Jin-Yong;Kim Jong-Ho
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2006.04a
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    • pp.391-393
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    • 2006
  • In this study, the performance of artificial neural network (ANN) models for estimating spatial distribution of water quality was evaluated using electric conductivity (EC) values in landfill site. For the ANN model development, feedforward neural networks and backpropagation algorithm with gradient descent method were used. In Test 1, the interpolation ability of the ANN model was evaluated. Results of the ANN model were more precise than those of the Kriging model. In Test 2, spatial distributions of EC values were predicted using precipitation data. Results seemed to be reasonable, however, they showed a limitation of ANN models in extrapolations.

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Discernment of Android User Interaction Data Distribution Using Deep Learning

  • Ho, Jun-Won
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.143-148
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    • 2022
  • In this paper, we employ deep neural network (DNN) to discern Android user interaction data distribution from artificial data distribution. We utilize real Android user interaction trace dataset collected from [1] to evaluate our DNN design. In particular, we use sequential model with 4 dense hidden layers and 1 dense output layer in TensorFlow and Keras. We also deploy sigmoid activation function for a dense output layer with 1 neuron and ReLU activation function for each dense hidden layer with 32 neurons. Our evaluation shows that our DNN design fulfills high test accuracy of at least 0.9955 and low test loss of at most 0.0116 in all cases of artificial data distributions.

Research on the geographic characteristics of the sea bed and the distribution of artificial reefs in Saran Bay (자란만의 해저지형 및 인공어초의 분포 조사 연구)

  • 김승철;신현옥
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.37 no.3
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    • pp.214-222
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    • 2001
  • A precise echosounding system to investigate the topographical characteristics of the coastal fishing ground was composed of a public-DGPS receiver, a single beam echosounder and a survey software. To confirm the usefulness of the system, a set-net fishing ground and the distribution of artificial reefs were surveyed. The results obtained are as follows : 1. The 2-D positioning error of the public-DGPS receiver with a DGPS mode and a GPS mode was 5.47 m, 7.03 m, respectively. 2. The experimented set-net fishing ground was located on the level ground at the depth of 9-10 m, a small size valley 1-2 m deep and approximately 10 m wide was found at a distance of 120 m from the set-net to the south. 3. In the artificial reefs' water area near the Jaran Bay, it was confirmed that twenty rectangular artificial reefs were established by the piece at the depth of 15-25 m and a natural reef 5-8 m high on the sea bed was located near the group of artificial reefs. 4. It was confirmed that the precise echosounding system was a useful tool in the pre-study to choice an appropriate water area to provide the artificial reef.

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Swarm Control of Distributed Autonomous Robot System based on Artificial Immune System using PSO (PSO를 이용한 인공면역계 기반 자율분산로봇시스템의 군 제어)

  • Kim, Jun-Yeup;Ko, Kwang-Eun;Park, Seung-Min;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.5
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    • pp.465-470
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    • 2012
  • This paper proposes a distributed autonomous control method of swarm robot behavior strategy based on artificial immune system and an optimization strategy for artificial immune system. The behavior strategies of swarm robot in the system are depend on the task distribution in environment and we have to consider the dynamics of the system environment. In this paper, the behavior strategies divided into dispersion and aggregation. For applying to artificial immune system, an individual of swarm is regarded as a B-cell, each task distribution in environment as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows: When the environmental condition changes, the agent selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other agent using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. In order to decide more accurately select the behavior strategy, the optimized parameter learning procedure that is represented by stimulus function of antigen to antibody in artificial immune system is required. In this paper, particle swarm optimization algorithm is applied to this learning procedure. The proposed method shows more adaptive and robustness results than the existing system at the viewpoint that the swarm robots learning and adaptation degree associated with the changing of tasks.