• 한국사회복지학
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• 제64권1호
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• pp.5-30
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• 2012

본 연구는 지역사회복지관의 주민조직 활동에서 지역주민이 구성한 언어를 토대로 주민조직과 참여자의 변화과정을 살펴봄으로써 근린지역사회조직화모델의 효과를 이해하기 위해 수행되었다. 연구결과 주민조직의 조직적, 개인적 차원에서의 변화과정을 확인할 수 있었다. 먼저 주민조직차원의 변화과정을 살펴보면 참여자들은 문제의 발견과 주민조직을 거쳐 조직의 목표를 설정하고 조직의 질적, 양적 변화의 의미를 구성한다. 개인적 차원에서 참여자들은 '갇힌 세계로부터의 탈출'을 거쳐 가치 있는 일을 통한 '나의 재구성'단계를 거치게 된다. 다음으로 참여자는 가족을 통해, 자신을 자랑스러운 존재로 재규정하고 있고 또한 이웃을 통해, '이웃은 곧 나'라는 새로운 의미를 구성한다. 마지막으로 연구결과를 토대로, 근린지역사회조직화모델의 효과를 높이기 위한 실천적 제언을 했다.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.23-28
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• 2021

The article discusses the features of adaptation of the parameters of the physical layer of data transmission in self-organizing networks based on unmanned aerial vehicles operating in the conditions of "smart cities". The concept of cities of this type is defined, the historical path of formation, the current state and prospects for further development in the aspect of transition to "smart cities" of the third generation are shown. Cities of this type are aimed at providing more comfortable and safe living conditions for citizens and autonomous automated work of all components of the urban economy. The perspective of the development of urban mobile automated technical means of infocommunications is shown, one of the leading directions of which is the creation and active use of wireless self-organizing networks based on unmanned aerial vehicles. The advantages of using small-sized unmanned aerial vehicles for organizing networks of this type are considered, as well as the range of tasks to be solved in the conditions of modern "smart cities". It is shown that for the transition to self-organizing networks in the conditions of "smart cities" of the third generation, it is necessary to ensure the adaptation of various levels of OSI network models to dynamically changing operating conditions, which is especially important for the physical layer. To maintain an acceptable level of the value of the bit error probability when transmitting command and telemetry data, it is proposed to adaptively change the coding rate depending on the signal-to-noise ratio at the receiver input (or on the number of channel decoder errors), and when transmitting payload data, it is also proposed to adaptively change the coding rate together with the choice of modulation methods that differ in energy and spectral efficiency. As options for the practical implementation of these solutions, it is proposed to use an approach based on the principles of neuro-fuzzy control, for which examples of determining the boundaries of theoretically achievable efficiency are given.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(A)
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• pp.254-255
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.394-394
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• 2000

This Paper proposes a new nonlinear partial least square method that extends the linear PLS. Proposed nonlinear PLS uses self-organizing feature map as PLS outer relation and multilayer neural network as PLS inner regression method.

• 전자공학회논문지C
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• 제34C권11호
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• pp.95-103
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• 1997

A robust center estimation tecnique of n-fold engineering parts is presented, which use self-organizing neural networks with generating and merging learning for training neural units. To estimate the center of the n-fold engineering parts using neural networks, the segmented boundaries of the interested part are approximated to strainght lines, and the temporal estimated centers by thecosine theorem which formed between the approximaged straight line and the reference point, , are indexed as (.sigma.-.theta.) parameteric vecstors. Then the entries of parametric vectors are fed into self-organizing nerual network. Finally, the center of the n-fold part is extracted by mean of generating and merging learning of the neurons. To accelerate the learning process, neural network uses an adaptive learning rate function to the merging process and a self-adjusting activation to generating process. Simulation results show that the centers of n-fold engineering parts are effectively estimated by proposed technique, though not knowing the error distribution of estimated centers and having less information of boundaries.

• 전자통신동향분석
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• 제38권6호
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• pp.95-106
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• 2023

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

• 융합신호처리학회논문지
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• 제2권3호
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• pp.79-85
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• 2001

본 논문에서는 퍼지 보상기와 자기구성 신경회로망을 이용하여 3축 매니퓰레이터의 역 기구학 해를 구하는 방법을 제안한다. 가우시안 위치 함수를 활성화 함수로 사용하는 자기구성 신경회로망은 학습 시작시 1개의 은닉층 노드를 가지고 학습을 하면서 점차적으로 은닉층의 노드수를 증가시킴으로서 최적의 노드수를 얻을 수 있으며, 퍼지 보상기는 신경회로망의 양호한 학습비를 얻는다. 이와 같이 시스템을 구성하여 빠른 학습속도와 학습비의 개선 그리고 빠른 정상상태로의 수렴을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.459-469
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• 2012

본 연구에서는 자기조직화 신경망이 필요한 노드만을 가지고 최적화하여 정규혼합분포를 추정하는 모형(Ahn과 Kim, 2011)을 Java언어에서 제공하는 스레드(thread)를 기반으로, 멀티코어 컴퓨팅환경에서 병렬처리방식으로 구현하여 순차처리방식에 비해 짧은 연산시간으로 정규혼합모형의 추정이 가능함을 보이려고 한다. 이를 위하여 Ahn과 Kim이 제안한 모형을 바탕으로 두 가지의 병렬처리 방법을 제안하고 그 성능을 평가하였다. 병렬처리 방법은 Java의 멀티스레드를 이용하여 구현되었으며, 모의실험을 통하여 제안한 모형이 순차처리방식과 비교하여 수렴속도가 빠름을 확인하였다.

• 제어로봇시스템학회논문지
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• 제10권12호
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• pp.1223-1232
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• 2004

We present a new technique to the design and real-time implementation of fuzzy control system basedon digital signal processors in order to improve the precision and robustness for system of industrial robot in this paper. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a Fuzzy Logic Controller, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult Self-Organizing Fuzzy Controller is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed Self-Organizing Fuzzy Controller scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.