• 제목/요약/키워드: Soft computing

검색결과 206건 처리시간 0.026초

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

  • Mandal, Sukomal;Rao, Subba;N., Harish;Lokesha, Lokesha
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제4권2호
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    • pp.112-122
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    • 2012
  • The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

Prediction of the static and dynamic mechanical properties of sedimentary rock using soft computing methods

  • Lawal, Abiodun I.;Kwon, Sangki;Aladejare, Adeyemi E.;Oniyide, Gafar O.
    • Geomechanics and Engineering
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    • 제28권3호
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    • pp.313-324
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    • 2022
  • Rock properties are important in the design of mines and civil engineering excavations to prevent the imminent failure of slopes and collapse of underground excavations. However, the time, cost, and expertise required to perform experiments to determine those properties are high. Therefore, empirical models have been developed for estimating the mechanical properties of rock that are difficult to determine experimentally from properties that are less difficult to measure. However, the inherent variability in rock properties makes the accurate performance of the empirical models unrealistic and therefore necessitate the use of soft computing models. In this study, Gaussian process regression (GPR), artificial neural network (ANN) and response surface method (RSM) have been proposed to predict the static and dynamic rock properties from the P-wave and rock density. The outcome of the study showed that GPR produced more accurate results than the ANN and RSM models. GPR gave the correlation coefficient of above 99% for all the three properties predicted and RMSE of less than 5. The detailed sensitivity analysis is also conducted using the RSM and the P-wave velocity is found to be the most influencing parameter in the rock mechanical properties predictions. The proposed models can give reasonable predictions of important mechanical properties of sedimentary rock.

Application of GMDH model for predicting the fundamental period of regular RC infilled frames

  • Tran, Viet-Linh;Kim, Seung-Eock
    • Steel and Composite Structures
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    • 제42권1호
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    • pp.123-137
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    • 2022
  • The fundamental period (FP) is one of the most critical parameters for the seismic design of structures. In the reinforced concrete (RC) infilled frame, the infill walls significantly affect the FP because they change the stiffness and mass of the structure. Although several formulas have been proposed for estimating the FP of the RC infilled frame, they are often associated with high bias and variance. In this study, an efficient soft computing model, namely the group method of data handling (GMDH), is proposed to predict the FP of regular RC infilled frames. For this purpose, 4026 data sets are obtained from the open literature, and the quality of the database is examined and evaluated in detail. Based on the cleaning database, several GMDH models are constructed and the best prediction model, which considers the height of the building, the span length, the opening percentage, and the infill wall stiffness as the input variables for predicting the FP of regular RC infilled frames, is chosen. The performance of the proposed GMDH model is further underscored through comparison of its FP predictions with those of existing design codes and empirical models. The accuracy of the proposed GMDH model is proven to be superior to others. Finally, explicit formulas and a graphical user-friendly interface (GUI) tool are developed to apply the GMDH model for practical use. They can provide a rapid prediction and design for the FP of regular RC infilled frames.

Robust Sentiment Classification of Metaverse Services Using a Pre-trained Language Model with Soft Voting

  • Haein Lee;Hae Sun Jung;Seon Hong Lee;Jang Hyun Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권9호
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    • pp.2334-2347
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    • 2023
  • Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

모바일기기를 위한 소프트키보드 인터페이스 디자인 (Soft Keyboard Interface Design for Mobile Device)

  • 오형용
    • 한국콘텐츠학회논문지
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    • 제7권6호
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    • pp.79-88
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    • 2007
  • 최근 유비쿼터스 컴퓨팅 환경이 점차 보급되면서 모바일 기기는 인간과 주변 환경간의 인터페이스 기기로서, 사용자와 정보를 주고받는 휴대용 단말기의 역할을 하고 있습니다. PDA(Personal Digital Assistants)나 스마트 폰과 같은 모바일 컴퓨터들은 우리 일상생활에서 점차 확대되어가고 있고, 이를 통해서 좀 더 많은 양의 데이터들을 입력하고자 하는 요구는 점점 늘어가고 있는 추세이다. 그러나, 보다 빠르고 많은 양의 문자 입력이 용이하게 설계되어진 이러한 alternative Soft-keyboard system들은 입력방식과 사용법이 큰 차이를 보이고 있고 더욱이 이러한 키보드들의 사용성이 충분히 검증되어 있지 않기 때문에 사용자들에게 많은 불편을 주고 있다. 본 논문은 한글 소프트 키보드의 GUI(Graphic User Interface)를 개선하기 위해 설문조사와 사용성 테스트를 통해 가이드라인을 제시하고자 하였고, 그 결과로 입력속도 향상과 GUI(Graphic User Interface) 개선을 위한 5개의 가이드라인을 도출하였다. 첫 번째로 QWERTY 키보드와의 유사성(familiarity), 그룹화 된 자판배열 보다는 독립된 키를 사용, 화면 내에서의 예상단어의 위치 고려, 즉각적 피드백(Prompt Feedback), 마지막으로 최적화된 키보드 사이즈의 고려이다.

승용차 A-Pillar Trim의 치수설계를 위한 소프트컴퓨팅기반 반응표면기법의 응용 (Application of Soft Computing Based Response Surface Techniques in Sizing of A-Pillar Trim with Rib Structures)

  • 김승진;김형곤;이종수;강신일
    • 대한기계학회논문집A
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    • 제25권3호
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    • pp.537-547
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    • 2001
  • The paper proposes the fuzzy logic global approximate optimization strategies in optimal sizing of automotive A-pillar trim with rib structures for occupant head protection. Two different strategies referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the inherent nonlinearity in analysis model should be accommodated over the entire design space and the training data is not sufficiently provided. The objective of structural design is to determine the dimensions of rib in A-pillar, minimizing the equivalent head injury criterion HIC(d). The paper describes the head-form modeling and head impact simulation using LS-DYNA3D, and the approximation procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and subsequently presents their generalization capabilities in terms of number of fuzzy rules and training data.

컴퓨터·정보(공)학 분야 공학교육인증제 운영성과에 대한 교수들의 인식 분석 및 개선방안 연구 (Study on the Analysis of the Recognition and Improvements by Professors for the CAC(Computing Engineering Committee))

  • 한지영;강소연;전주현
    • 공학교육연구
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    • 제19권5호
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    • pp.35-47
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    • 2016
  • This study analyzed outcomes of CAC(Computing Accreditation Committee) program individually applied in the field of computing engineering since 2007, and draw improvements. Literature review through academic journals, survey research and the FGI(Focus Group Interview) were used to accomplish objectives of the study. In addition, the survey research and FGI were done for professors. For the survey research, nationally 20 out of 44 universities which operates the CAC program were investigated, and sample universities were considered by region. FGI was done to analyze the performance and problems of CAC in more detail for 6 experts. Results of the study were follows as; first, CAC program was activated through the Seoul Accord activation support business by government. Second, BSM(Basic Science and Math), engineering major and engineering design education have been strengthened compared with before and after of CAC introduction in the computing engineering field. Third, soft skills needed for students in the college of engineering have been organized in the professional general curriculum, and professors aware of improvement of ability of the students for the skills. The degree of satisfaction for the CAC program has been examined as normal level, but improvement of educational system and the overall quality enhancement of computing engineering education were affected by CAC program. Nonetheless of positive results of CAC program, incentive system for certification program graduates, the expansion of the autonomy of the department, reduction in the amount of self-evaluation report, and support of administrative human resources were suggested for taking root successfully of CAC program.

가우스 적분법을 이용한 압밀침하량 산정 (Evaluation of Consolidation Settlement by Gaussian Quadrature)

  • 윤찬영;정영훈
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2009년도 춘계 학술발표회
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    • pp.188-194
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    • 2009
  • Consolidation settlement, a crucial parameter in geotechnical design of soft ground, has not been computed in a unique way due to different computation methods in practice. To improve computational error in calculating consolidation settlement, a number of researches has been attempted. Conventional 1-dimensional consolidation theory assumes the center of the clay layer as the representative point to obtain effective stress in calculation, which could resort to erroneous results. To calculate exact solutions considering initial distribution of effective stress, diving a stratum into multi-layers could resort to wasting time and effort. In the study, a novel methodology for calculating consolidation settlement via Guassian quadrature is developed. The method generally is capable of computing settlements in any case of the stress conditions encountered in fields.

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컨벌루션 함수를 이용한 자동두께측정 영상의 성능분석 (Performance Analysis of Automatic Thickness Image using Convolution Function)

  • 강민구;조문신
    • 인터넷정보학회논문지
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    • 제11권1호
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    • pp.21-26
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    • 2010
  • 본 논문에서는 LCD TV용 필름의 균일성을 개선하고자, 소프트 엑스레이(soft X-ray)를 이용하여 볼트 연결기법과 컨벌루션(convolution) 함수기반의 영상처리를 결합한다. 필름의 프로파일에서 두께를 측정하는 라인 스캔과정에서 선원 변경 시 오프셋 오류가 발생한다. 이러한 선원의 오프셋 오류를 제거하고자, 인접한 3개 볼트의 영상에 대해 컨벌루션 함수를 적용함으로써 자동으로 두께 측정이 가능하고, 영상분석 성능을 향상한다.

SSD를 위한 Soft RAID 저장 시스템 설계 (Design of Soft RAID Storage System for SSD(Solid State Disk))

  • 변시우;허문행;노창배;김덕태
    • 한국산학기술학회:학술대회논문집
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    • 한국산학기술학회 2008년도 춘계학술발표논문집
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    • pp.218-219
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    • 2008
  • Solid State Disks(SSD) are one of the best candidates to support next storage technology in desktop and server computing environment. The features of non-volatility, low power consumption, and fast access time for read operations are sufficient grounds to support SSD as major components of future storages. This paper describes a technical trend of HDD based RAID technology and proposes a new RAID system for SSD.

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