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Practical autoencoder based anomaly detection by using vector reconstruction error

Cybersecurity 2023年第2期6卷 1-13页

作者： hasan torabi Seyedeh Leili Mirtaheri Sergio Greco Department of Electrical and Computer Engineering Faculty of EngineeringKharazmi UniversityTehranIran Department of Informatics ModelingElectronics and System EngineeringUniversity of CalabriaArcavacataItaly.

Nowadays,cloud computing provides easy access to a set of variable and configurable computing resources based on user demand through the *** computing services are available through common internet protocols and network standards.n addition to the unique benefits of cloud computing,insecure communication and attacks on cloud networks cannot be *** are several techniques for dealing with network *** this end,network anomaly detection systems are widely used as an effective countermeasure against network *** anomaly-based approach generally learns normal traffic patterns in various ways and identifies patterns of *** anomaly detection systems have gained much attention in intelligently monitoring network traffic using machine learning *** paper presents an efficient model based on autoencoders for anomaly detection in cloud computing *** autoencoder learns a basic representation of the normal data and its reconstruction with minimum ***,the reconstruction error is used as an anomaly or classification *** addition,to detecting anomaly data from normal data,the classification of anomaly types has also been *** have proposed a new approach by examining an autoencoder's anomaly detection method based on data reconstruction *** the existing autoencoder-based anomaly detection techniques that consider the reconstruction error of all input features as a single value,we assume that the reconstruction error is a *** enables our model to use the reconstruction error of every input feature as an anomaly or classification *** further propose a multi-class classification structure to classify the *** use the CIDDS-001 dataset as a commonly accepted dataset in the *** evaluations show that the performance of the proposed method has improved considerably compared to the existing ones in terms of accuracy,recall,false-positive rate,and F1-score

关键词： Cloud Practical Anomaly detection Autoencoder Reconstruction error Machine learning

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Predication of discharge coefficient of cylindrical weir- gate using adaptive neuro fuzzy inference systems （ANFIS）

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Frontiers of Structural and Civil Engineering 2017年第1期11卷 111-122页

作者： Abbas PARSAIE Amir Hamzeh HAGHIABI Mojtaba SANEIE hasan torabi Department of Water Engineering Lorestan University Khorramabad Iran Soil Conservation and Watershed Management Research Institute Tehran Iran

Settlement of sediments behind weirs and accumulation of materials floating on water behind gates decreases the performance of these structures. Weir-gate is a combination of weir and gate structures which solves them Infirmities. Proposing a circular shape for crest of weirs to improve their performance, investigators have proposed cylindrical shape to improve the performance of weir-gate structure and call it cylindrical weir-gate. In this research, discharge coefficient of weir-gate was predicated using adaptive neuro fuzzy inference systems （ANFIS）. To compare the performance of ANFIS with other types of soft computing techniques, multilayer perceptron neural network （MLP） was prepared as well. Results of MLP and ANFIS showed that both models have high ability for modeling and predicting discharge coefficient; however, ANFIS is a bit more accurate. The sensitivity analysis of MLP and ANFIS showed that Froude number of flow at upstream of weir and ratio of gate opening height to the diameter of weir are the most effective parameters on discharge coefficient.

关键词： weir-gate soft computing crest geometry circular crest weir cylindrical shape

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Experimental study of the velocity of density currents in convergent and divergent channels

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International Journal of Sediment Research 2014年第4期29卷 518-523页

作者： hasan torabi POUDEH Samad EMAMGHOLIZADEH Manoocher Fathi-MOGHADAM Department of Water Engineering Lorestan of University Department of Water and Soil Engineering University of Shahrood Department of Hydraulic Structures Shahid Chamran University

The head velocity of the density current in the convergent and divergent channel is a key parameter for evaluating the extent to which suspended material travels,and for determining the type and distribution of sediment in the water *** study experimentally evaluated the effects of the reach degree of convergence and divergence on the head velocity of the density *** were conducted in the flume with 6.0 m long,0.72 m width and 0.6 m *** head velocity was measured at three convergent degrees(-8°;-12°;-26°),at three divergent degrees(8°;12°;26°) and two slopes(0.009,0.016) for various *** measured head velocity of the density current is compared with the head velocity of the density current in the constant cross section *** on non-dimensional and statistical analysis,relations as linear multiple regression are offered for predicting head velocity of the density current in the convergent,divergent and constant cross section *** the results of this research show that for the same slope and discharge,the head velocity of the density current in the convergent and divergent channel are greater and less than the head velocity of the constant cross section,respectively.

关键词： Density current Divergent and convergent channel Reservoir Sediment

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Experimental study of the velocity of density currents in convergent and divergent channels

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International Journal of Sediment Research 2013年第2期28卷 254-259页

作者： hasan torabi POUDEH Samad EMAMGHOLIZADEH Manoocher Fathi-MOGHADAM Department of Water Engineering Lorestan of University Department of Water and Soil Engineering Shahrood University of Technology Department of Hydraulic Structures Shahid Chamran University

The head velocity of the density current in the convergent and divergent channel is a key parameter for evaluating the extent to which suspended material travels,and for determining the type and distribution of sediment in the water *** study experimentally evaluated the effects of the reach degree of convergence and divergence on the head velocity of the density *** were conducted in the flume with 6.0 m long,0.72 m width and 0.6 m *** head velocity was measured at three convergent degrees(-8°;-12°;-26°),at three divergent degrees(8°;12°;26°) and two slopes(0.009,0.016) for various *** measured head velocity of the density current is compared with the head velocity of the density current in the constant cross section channel. Based on non-dimensional and statistical analysis,relations as linear multiple regression offered for prediction head velocity of the density current in the convergent,divergent and constant cross section *** the results of this research show that for the same slope and discharge,the head velocity of the density current in the convergent and divergent channel are greater and less than the head velocity of the constant cross section, respectively.

关键词： Density current Divergent and convergent channel Reservoir Sediment

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Optimization of the Water Distribution Networks with Differential Evolution (DE) and Mixed Integer Linear Programming (MILP)

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Journal of Water Resource and Protection 2015年第9期7卷 715-729页

作者： Ramin Mansouri hasan torabi Mohammd Hoseini Hosein Morshedzadeh Water Engineering Department Lorestan University Khoram Abad Iran Economics and Management Department Tehran University Tehran Iran

Nowadays, due to increasing population and water shortage and competition for its consumption, especially in the agriculture, which is the largest consumer of water, proper and suitable utilization and optimal use of water resources is essential. One of the important parameters in agriculture field is water distribution network. In this research, differential evolution algorithm (DE) was used to optimize Ismail Abad water supply network. This network is pressurized network and includes 19 pipes and 18 nodes. Optimization of the network has been evaluated by developing an optimization model based on DE algorithm in MATLAB and the dynamic connection with EPANET software for network hydraulic calculation. The developing model was run for the scale factor (F), the crossover constant (Cr), initial population (N) and the number of generations (G) and was identified best adeptness for DE algorithm is 0.6, 0.5, 100 and 200 for F and Cr, N and G, respectively. The optimal solution was compared with the classical empirical method and results showed that implementation cost of the network by DE algorithm was 10.66% lower than the classical empirical method.

关键词： Differential Evolution Algorithm Optimization Distribution Systems Crossover Constant Scale Factor

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