Search Results - (( pattern detection method algorithm ) OR ( using simulation method algorithm ))
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column
Published 2003“…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. …”
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…In this paper, a â��butterflyâ�� shape derived from the manipulation of the standard PV and OP data, which is more robust towards different loop dynamics, is developed for stiction detection. This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
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Identifying multiple outliers in linear functional relationship model using a robust clustering method
Published 2023“…Application in real data also shows that the proposed clustering method for this linear functional relationship model successfully detects the outliers, thus suggesting the method’s practicality in real-world problems.…”
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Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni
Published 2018“…The finalized configuration that resulted in the best response was adopted and used to collect data for training and classifying the gait phase using pattern recognition method. …”
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Neuro fuzzy classification and detection technique for bioinformatics problems
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Effective source number enumeration approach under small snapshot numbers
Published 2024“…The method first uses the SEMD method to decompose the array signal, decomposing the complex signal into several Intrinsic Mode Functions (IMFs), and then extracts features through these IMFs to estimate the number of signal sources. …”
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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki
Published 2014“…A novel investigation in modelling of groundwater level and quality using Artificial Neural Networks (ANNs) and Adaptive neuro fuzzy inference systems (ANFIS) methods was developed in the study area. …”
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Embedded wearable EEG seizure detection in ambulatory state
Published 2014“…This paper describes a classification method is presented using a Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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A coded aperture-based 3D SPECT imaging system for early breast cancer detection
Published 2023“…Instead of a collimator, this study proposes a coded aperture (CA) based SPECT imaging system where a mask is attached to a typical clinical gamma camera. This imaging method investigates different patterns of the Modified Uniformly Redundant Array (MURA) masks and mosaic MURA masks by a simulating point source, planar source, and the 3D realistic anthropomorphic female breast phantom. …”
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Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region
Published 2018“…The modification also aids in constructing an integrated model that is able to not only detect the nonlinearity in the training data but also the wide range of features within the training data records used to simulate the forecasting model. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…Plots of survival distribution function against failure time are used to examine the predicted survival patterns for the two types of failures. …”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State
Published 2014“…This paper describes a classification method is presented using an Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…However, the current research state is unsatisfactory, especially in terms of structural design, robot system and the robot control method. In this research, an EMG controlled 3D printed robot hand prototype with improved features and advance hand posture classification method based on EMG signal pattern were proposed. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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