Effect of unbraced excavation in clayey soil on adjacent buildings

Research Abstract
NULL
Research Authors
E.H. Ramadan, M. H. Hussein, A. A. Senoon and Ahmed A. Mohmed
Research Department
Civil Engineering Department
Research Journal
In : Proceeding of the 17th International Conference on Soil Mechanics and Geotechnical Engineering, Alexandria, Egypt,
Research Member
Ibrahim Hassan Ramadan Mahjob
Research Pages
pp 1774-177
Research Publisher
NULL
Research Rank
4
Research Vol
NULL
Research Website
NULL
Research Year
2009

Passive earth pressure against retaining wall using log-spiral arc.

Research Abstract
NULL
Research Authors
Senoon , A. A.
Research Department
Civil Engineering Department
Research Journal
Journal of Engineering Sciences, Faculty of Engineering, University of Assiut
Research Member
Abdelziz Ahmed Ali Hassan
Research Pages
pp. 113-135
Research Publisher
NULL
Research Rank
2
Research Vol
Vol. 41- No. 1
Research Website
NULL
Research Year
2013

Supporting Excavation in Soft Clay using Pile Wall System

Research Abstract
NULL
Research Authors
Abedel-Aziz A. A. Senoon , Hanna Abo-Dahab and Ashraf Abo-Elwafa
Research Department
Civil Engineering Department
Research Journal
Proceeding in International Conference on Structural and Geotechnical Engineering, Ain Shams University ICSGE 14. Cairo, Egypt
Research Member
Ashraf Abo AlWafa Mohamed AbdelHafez Mohamed
Research Pages
NULL
Research Publisher
NULL
Research Rank
4
Research Vol
NULL
Research Website
NULL
Research Year
2015

Supporting Excavation in Soft Clay using Pile Wall System

Research Abstract
NULL
Research Authors
Abedel-Aziz A. A. Senoon , Hanna Abo-Dahab and Ashraf Abo-Elwafa
Research Department
Civil Engineering Department
Research Journal
Proceeding in International Conference on Structural and Geotechnical Engineering, Ain Shams University ICSGE 14. Cairo, Egypt
Research Member
Abdelziz Ahmed Ali Hassan
Research Pages
NULL
Research Publisher
NULL
Research Rank
4
Research Vol
NULL
Research Website
NULL
Research Year
2015

Effect of Stone Density and Stone Cushion on the Behavior of Soft Soils Improved by Stone Columns

Research Abstract
NULL
Research Authors
Ebraheem Hasan Ramadan, Abdel-Aziz A. A. H. Senoon, Mohammed M. A. Hussein and Diaa-Eldin A. Kotp
Research Department
Civil Engineering Department
Research Journal
Life Science Journal
Research Member
Ibrahim Hassan Ramadan Mahjob
Research Pages
pp 19-30
Research Publisher
NULL
Research Rank
2
Research Vol
Vol. 13 - No. 4
Research Website
NULL
Research Year
2016

Effect of Stone Density and Stone Cushion on the Behavior of Soft Soils Improved by Stone Columns

Research Abstract
NULL
Research Authors
Ebraheem Hasan Ramadan, Abdel-Aziz A. A. H. Senoon, Mohammed M. A. Hussein and Diaa-Eldin A. Kotp
Research Department
Civil Engineering Department
Research Journal
Life Science Journal
Research Member
Abdelziz Ahmed Ali Hassan
Research Pages
pp 19-30
Research Publisher
NULL
Research Rank
2
Research Vol
Vol. 13 - No. 4
Research Website
NULL
Research Year
2016

Implementation of Fuzzy and Adaptive Neuro-Fuzzy Inference Systems in Optimization of Production Inventory Problem

Research Abstract
Most of the earlier studies in the inventory control and management make assumption that the manufacturing system is reliable and does not fail. However, in the real industrial applications, there is no completely reliable manufacturing system; Machine failure occur and the production does not resume before repair. In this paper, we will study and analyze the optimal lot size in a real production system which is not completely reliable. To obtain the optimal production quantity. Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been used for modeling and simulation. This approach combines the advantages of rule-base fuzzy system and the learning capability benefit of neural networks. In the case study of cement industry, ANFIS prediction has shown very good agreement with the real production quantity. This model can be extended for any inventory production quantity problems if the industrial data are available.
Research Authors
Ahmed Abdel-Aleem, Mahmoud A. El-Sharief, Mohsen A. Hassan and Mohamed G. El-Sebaie
Research Journal
Applied Mathematics & Information Sciences
Research Member
Mohamed Gad Elsebahe KarmAllh
Research Pages
pp. 289–298
Research Publisher
Natural Sciences Publishing
Research Rank
1
Research Vol
vol. 11, no. 1
Research Website
http://www.naturalspublishing.com/Article.asp?ArtcID=12616
Research Year
2017

Implementation of Fuzzy and Adaptive Neuro-Fuzzy Inference Systems in Optimization of Production Inventory Problem

Research Abstract
Most of the earlier studies in the inventory control and management make assumption that the manufacturing system is reliable and does not fail. However, in the real industrial applications, there is no completely reliable manufacturing system; Machine failure occur and the production does not resume before repair. In this paper, we will study and analyze the optimal lot size in a real production system which is not completely reliable. To obtain the optimal production quantity. Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been used for modeling and simulation. This approach combines the advantages of rule-base fuzzy system and the learning capability benefit of neural networks. In the case study of cement industry, ANFIS prediction has shown very good agreement with the real production quantity. This model can be extended for any inventory production quantity problems if the industrial data are available.
Research Authors
Ahmed Abdel-Aleem, Mahmoud A. El-Sharief, Mohsen A. Hassan and Mohamed G. El-Sebaie
Research Journal
Applied Mathematics & Information Sciences
Research Member
Mohsen AbdelNaeim Hassan Mohamed
Research Pages
pp. 289–298
Research Publisher
Natural Sciences Publishing
Research Rank
1
Research Vol
vol. 11, no. 1
Research Website
http://www.naturalspublishing.com/Article.asp?ArtcID=12616
Research Year
2017

Implementation of Fuzzy and Adaptive Neuro-Fuzzy Inference Systems in Optimization of Production Inventory Problem

Research Abstract
Most of the earlier studies in the inventory control and management make assumption that the manufacturing system is reliable and does not fail. However, in the real industrial applications, there is no completely reliable manufacturing system; Machine failure occur and the production does not resume before repair. In this paper, we will study and analyze the optimal lot size in a real production system which is not completely reliable. To obtain the optimal production quantity. Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been used for modeling and simulation. This approach combines the advantages of rule-base fuzzy system and the learning capability benefit of neural networks. In the case study of cement industry, ANFIS prediction has shown very good agreement with the real production quantity. This model can be extended for any inventory production quantity problems if the industrial data are available.
Research Authors
Ahmed Abdel-Aleem, Mahmoud A. El-Sharief, Mohsen A. Hassan and Mohamed G. El-Sebaie
Research Journal
Applied Mathematics & Information Sciences
Research Member
Mahmoud Ahmed Abdullah Ahmed El-Sharief
Research Pages
pp. 289–298
Research Publisher
Natural Sciences Publishing
Research Rank
1
Research Vol
vol. 11, no. 1
Research Website
http://www.naturalspublishing.com/Article.asp?ArtcID=12616
Research Year
2017
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