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All Journal Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII
Risaldi Hidayat
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Transportation

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A Review of Artificial Intelligent for Prediction Ground Vibration in Blasting Risaldi Hidayat; Tedy Agung Cahyadi; Eddy Winarno; Singgih Saptono; S. Koesnaryo
Retii 2020: Prosiding Seminar Nasional ReTII ke-15
Publisher : Institut Teknologi Nasional Yogyakarta

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Abstract

Blasting activities cause ground vibrations that affect the potential for ground displacement in surface mining. That will have an impact on the stability of the slope and environmental problems. Therefore, it is necessary to analyze the prediction ground vibrations measured by peak particle velocity (PPV). Artificial Intelligent (AI) has an important role to overcome the limitations of parameters used, uncertainty, and inaccuracy than conventional methods. AI for prediction ground vibration has grown a lot in recent years. To find out an accurate and effective AI technique, the authors compare several techniques by evaluating their strengths and weaknesses based on literature studies. The ICA-M5Rules model and ICA-ANN model are techniques that have high accuracy and flexibility of use than other presented techniques. And related to the use of parameters, there are other parameters that play an important role which will be reviewed in this journal.
A Review of Slope Stability Analysis Using Artificial Neural Networks Risaldi Hidayat
Retii 2022: Prosiding Seminar Nasional ReTII ke-17
Publisher : Institut Teknologi Nasional Yogyakarta

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Over the last few years, arificial neural network (ANN) have been used successfully for modeling almost all aspect of geotechnical engineering problems especially in slope stability. Based on the comparison in this paper, that ANN has many advantages if the problem cannot be solved by mathematically and handle large data set. There are various intelligent algorithms available, therefore ANN is not a new concept. However, ANN's ability to solve complex geotechnical engineering problems (such as, which is found within the slope stability analysis) is its main advantage. So, this paper to provide an overview of ANN modeling in slope stability analysis as part of geotechnical engineering problems and research direction of ANN that needs further attention in the future.
Co-Authors Cahyadi, Tedy Agung Eddy Winarno S. Koesnaryo Singgih Saptono, Singgih