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Research paper thumbnail of A novel neural-evolutionary framework for predicting weight on the bit in drilling operations

Scientific Reports

This study compares the performance of artificial neural networks (ANN) trained by grey wolf opti... more This study compares the performance of artificial neural networks (ANN) trained by grey wolf optimization (GWO), biogeography-based optimization (BBO), and Levenberg–Marquardt (LM) to estimate the weight on bit (WOB). To this end, a dataset consisting of drilling depth, drill string rotational speed, rate of penetration, and volumetric flow rate as input variables and the WOB as a response is used to develop and validate the intelligent tools. The relevance test is applied to sort the strength of WOB dependency on the considered features. It was observed that the WOB has the highest linear correlation with the drilling depth and drill string rotational speed. After dividing the databank into the training and testing (4:1) parts, the proposed LM-ANN, GWO-ANN, and BBO-ANN ensembles are constructed. A sensitivity analysis is then carried out to find the most powerful structure of the models. Each model performs to reveal the relationship between the WOB and the mentioned independent fa...

Research paper thumbnail of Simultaneous Multiple Sensor, Fusion, Classification and Moving Obstacles traction Using Bayesian Algorithm based on extended Dempster-Shafer Theory

HAL (Le Centre pour la Communication Scientifique Directe), May 13, 2019

Research paper thumbnail of Improvements In Edge Detection Based On Mathematical Morphology And Wavelet Transform Using Fuzzy Rules

In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical mo... more In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical morphology and wavelet transform is proposed. The combined method is proposed to overcome the limitation of wavelet based edge detection and mathematical morphology based edge detection in noisy images. Experimental results show superiority of the proposed method, as compared to the traditional Prewitt, wavelet based and morphology based edge detection methods. The proposed method is an effective edge detection method for noisy image and keeps clear and continuous edges.

Research paper thumbnail of Human Skin Detection by Designing a Fuzzy System in Color Space

one of the issues which are dealt with as an important issue in identification of a human in imag... more one of the issues which are dealt with as an important issue in identification of a human in images is skin detection. Human skin detection with suitable speed and high accuracy is very necessary and very valuable in promoting quality of detection and can give suitable features for more correct detection. In this paper, a new fuzzy method is studied to identify human skin based on YCBCR colorful model. Skin color in YCBCR space forms a continuous set. Considering histogram of continuous set in color space, suitable membership functions are considered for fuzzy system. Based on inputs of fuzzy system, decision is made about each pixel. Tests have been performed on fei database and the obtained results show accuracy of 97% on test images. Humans see each other and remember each other based on memorization of a series of features. Human mind detects and identifies different humans based on extraction of a series of features and its adaption to the surrounding environments. Face detecti...

Research paper thumbnail of Providing a multi-objective scheduling tasks by Using PSO algorithm for cost management in cloud computing

International Journal of Computer Applications Technology and Research, 2016

This article is intended to use the multi-PSO algorithm for scheduling tasks for cost management ... more This article is intended to use the multi-PSO algorithm for scheduling tasks for cost management in cloud computing. This means that any migration costs due to supply failure consider as a one objective and each task is a little particle and recognize by use of the appropriate fitness schedule function (how the particles arrangement) that cost at least amount of total expense. In addition to, the weight is granted to the each expenditure that reflects the importance of cost. The data which is used to simulate proposed method are series of academic and research data that are prepared from the Internet and MATLAB software is used for simulation. We simulate two issues, in the first issue, consider four task by four vehicles and divide tasks. In the second issue, make the issue more complicated and consider six tasks by four vehicles. We write PSO's output for each two issues of various iterations. Finally, the particles dispersion and as well as the output of the cost function were computed for each part.

Research paper thumbnail of Fusión, clasificación y tracción simultáneas de obstáculos en movimiento mediante LIDAR y cámara usando algoritmo bayesiano

Innovaciencia Facultad de Ciencias Exactas Físicas y Naturales, 2020

In the near future, preventing collisions with fixed or moving, alive, and inanimate obstacles wi... more In the near future, preventing collisions with fixed or moving, alive, and inanimate obstacles will appear to be a severe challenge due to the increased use of Unmanned Ground Vehicles (UGVs). Light Detection and Ranging (LIDAR) sensors and cameras are usually used in UGV to detect obstacles. The definite tracing and classification of moving obstacles is a significant dimension in developed driver assistance systems. It is believed that the perceived model of the situation can be improved by incorporating the obstacle classification. The present study indicated a multi-hypotheses monitoring and classifying approach, which allows solving ambiguities rising with the last methods of associating and classifying targets and tracks in a highly volatile vehicular situation. This method was tested through real data from various driving scenarios and focusing on two obstacles of interest vehicle, pedestrian.

Research paper thumbnail of A novel neural-evolutionary framework for predicting weight on the bit in drilling operations

Scientific Reports

This study compares the performance of artificial neural networks (ANN) trained by grey wolf opti... more This study compares the performance of artificial neural networks (ANN) trained by grey wolf optimization (GWO), biogeography-based optimization (BBO), and Levenberg–Marquardt (LM) to estimate the weight on bit (WOB). To this end, a dataset consisting of drilling depth, drill string rotational speed, rate of penetration, and volumetric flow rate as input variables and the WOB as a response is used to develop and validate the intelligent tools. The relevance test is applied to sort the strength of WOB dependency on the considered features. It was observed that the WOB has the highest linear correlation with the drilling depth and drill string rotational speed. After dividing the databank into the training and testing (4:1) parts, the proposed LM-ANN, GWO-ANN, and BBO-ANN ensembles are constructed. A sensitivity analysis is then carried out to find the most powerful structure of the models. Each model performs to reveal the relationship between the WOB and the mentioned independent fa...

Research paper thumbnail of Simultaneous Multiple Sensor, Fusion, Classification and Moving Obstacles traction Using Bayesian Algorithm based on extended Dempster-Shafer Theory

HAL (Le Centre pour la Communication Scientifique Directe), May 13, 2019

Research paper thumbnail of Improvements In Edge Detection Based On Mathematical Morphology And Wavelet Transform Using Fuzzy Rules

In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical mo... more In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical morphology and wavelet transform is proposed. The combined method is proposed to overcome the limitation of wavelet based edge detection and mathematical morphology based edge detection in noisy images. Experimental results show superiority of the proposed method, as compared to the traditional Prewitt, wavelet based and morphology based edge detection methods. The proposed method is an effective edge detection method for noisy image and keeps clear and continuous edges.

Research paper thumbnail of Human Skin Detection by Designing a Fuzzy System in Color Space

one of the issues which are dealt with as an important issue in identification of a human in imag... more one of the issues which are dealt with as an important issue in identification of a human in images is skin detection. Human skin detection with suitable speed and high accuracy is very necessary and very valuable in promoting quality of detection and can give suitable features for more correct detection. In this paper, a new fuzzy method is studied to identify human skin based on YCBCR colorful model. Skin color in YCBCR space forms a continuous set. Considering histogram of continuous set in color space, suitable membership functions are considered for fuzzy system. Based on inputs of fuzzy system, decision is made about each pixel. Tests have been performed on fei database and the obtained results show accuracy of 97% on test images. Humans see each other and remember each other based on memorization of a series of features. Human mind detects and identifies different humans based on extraction of a series of features and its adaption to the surrounding environments. Face detecti...

Research paper thumbnail of Providing a multi-objective scheduling tasks by Using PSO algorithm for cost management in cloud computing

International Journal of Computer Applications Technology and Research, 2016

This article is intended to use the multi-PSO algorithm for scheduling tasks for cost management ... more This article is intended to use the multi-PSO algorithm for scheduling tasks for cost management in cloud computing. This means that any migration costs due to supply failure consider as a one objective and each task is a little particle and recognize by use of the appropriate fitness schedule function (how the particles arrangement) that cost at least amount of total expense. In addition to, the weight is granted to the each expenditure that reflects the importance of cost. The data which is used to simulate proposed method are series of academic and research data that are prepared from the Internet and MATLAB software is used for simulation. We simulate two issues, in the first issue, consider four task by four vehicles and divide tasks. In the second issue, make the issue more complicated and consider six tasks by four vehicles. We write PSO's output for each two issues of various iterations. Finally, the particles dispersion and as well as the output of the cost function were computed for each part.

Research paper thumbnail of Fusión, clasificación y tracción simultáneas de obstáculos en movimiento mediante LIDAR y cámara usando algoritmo bayesiano

Innovaciencia Facultad de Ciencias Exactas Físicas y Naturales, 2020

In the near future, preventing collisions with fixed or moving, alive, and inanimate obstacles wi... more In the near future, preventing collisions with fixed or moving, alive, and inanimate obstacles will appear to be a severe challenge due to the increased use of Unmanned Ground Vehicles (UGVs). Light Detection and Ranging (LIDAR) sensors and cameras are usually used in UGV to detect obstacles. The definite tracing and classification of moving obstacles is a significant dimension in developed driver assistance systems. It is believed that the perceived model of the situation can be improved by incorporating the obstacle classification. The present study indicated a multi-hypotheses monitoring and classifying approach, which allows solving ambiguities rising with the last methods of associating and classifying targets and tracks in a highly volatile vehicular situation. This method was tested through real data from various driving scenarios and focusing on two obstacles of interest vehicle, pedestrian.