Asian Journal of Civil Engineering -

Sujet:	Early View

Articles dans ce numéro

Auteur(s)	Titre	Page(s)
Kannadasan, B. / Yogeswari, K.	ANN-based traffic planning model using adaptive YOLOv5-aided object counting from surveillance videos
Mustafa, Rashid / Ahmad, Md Talib	Appraisal of numerous machine learning techniques for the prediction of axial load carrying capacity of rectangular concrete column
Hussein Al-Juboori, Mohammed J. / Kadhim, Muhammad Jawad	Behavior of reinforced concrete inverted T-girders with hollow webs strengthened by CFRP sheets in flexure
Jangam, Tanmay / Kumbhar, Popat	Comparative behaviour of ‘conventional’ and ‘pre-engineered’ industrial structures with diagonal bracings considering smaller and larger openings
Sapkota, Ashish / Sapkota, Binod / Poudel, Jhabindra / Giri, Suyog	Comparative study on the seismic performance of a typical low-rise building in Nepal using different seismic codes
Gulati, Ritu / Bano, Samreen / Bano, Farheen / Singh, Sumit / Singh, Vikash	Compressive strength of concrete formulated with waste materials using neural networks
Rahman, Taimur / Sultana, Shamima / Ahmed, Tanjir / Momin, Md. Farhad / Provasha, Afra Anam	Deep symbolic regression for numerical formulation of fundamental period in concentrically steel-braced RC frames
Sethi, Krushna Chandra / Rathinakumar, V. / Harishankar, S. / Bhadoriya, Gautam / Pati, Aditya Kumar	Development of discrete opposition-based NSGA-III model for optimizing trade-off between discrete time, cost, and resource in construction projects
Agarwal, Aditya Kumar / Chauhan, Shyamveer Singh / Sharma, Kamal / Sethi, Krushna Chandra	Development of time–cost trade-off optimization model for construction projects with MOPSO technique
Pathak, Sudhanshu S. / Vesmawala, Gaurang R. / Mane, Sachin J. / Sarnobat, Sandeep S.	Effectiveness of artificial neural network for forecasting of fracture toughness of concrete specimens
Alkhadrawi, Sajeda / Alzboon, Kamel K.	Enhancing Water treatment predictions: a Machine Learning Approach with CNN and Water Wave optimization
Patil, Rupali A. / Salgar, Pramod B.	Experimental investigation on structural behaviour of castellated column under axial load
Kashyap, Rishabh / Saxena, Mukul / Gautam, Arstu / Kushwaha, Anuj / Priyanka, Km. / Patel, Anubhav / Maurya, Rajneesh Kumar	Exploring sustainable construction through experimental analysis and AI predictive modelling of ceramic waste powder concrete
Sasikumar, P. / Manju, R.	Flexural behaviour and strengthening of reinforced concrete beams using concrete canvas
Moradi, Nima / Yazdani, Mahdi / Janbozorgi, Fatemeh / Hashemi, Seyed Jafar	In-plane seismic performance of historical masonry walls with various brick bond patterns using micro-modeling approach
Shrivastava, Ankit / Pandey, Mukesh	Integrating quality in resource-constrained time-cost trade-off optimization for civil construction projects using NSGA-III technique
Patil, Rupali A. / Salgar, Pramod B.	An investigation for enhancing seismic performance of high-rise buildings using fluid viscous damper (FVD)
Ergen, Faruk / Katlav, Metin	Machine and deep learning-based prediction of flexural moment capacity of ultra-high performance concrete beams with/out steel fiber
Dunin, Abbas Abdulkarim / Hosseinlou, Farhad / Labibzadeh, Mojtaba / Rezaeian, Abbas	A new approach to retrofit the diagrid structures using an improved outrigger-braced system
Jadhav, Sanjivani Dhanaji / Kumbhar, Popat Dattatraya	Non-linear behavior of castellated beams consisting hexagonal and diamond openings using CFRP stiffeners
Afzal Khan, Kaleem / Khan, Shahzada / Gul, Akhtar / Waqas, Hafiz Ahmed / Ilyas, Muhammad	Numerical modeling and parametric study of hollow reinforced concrete slabs for flexural behavior
Manchalwar, Atulkumar / Ganpule, Sneha / Patil, Ashwini	Optimal allocation of non-linear viscous dampers for building structures
Kumar Tipu, Rupesh / Batra, Vandna / Panchal, V. R. / Pandya, K. S. / Patel, Gaurang A.	Optimizing compressive strength in sustainable concrete: a machine learning approach with iron waste integration
Pham, Vu Hong Son / Huynh, Loc Tin	Optimizing multi-objective construction management for resource-constrained project scheduling problems: a bio-inspired approach
Malathy, R. B. / Bhatt, Govardhan / Chowdhury, Sagar	Parametric study of blast loads on structures
Sathiparan, Navaratnarajah	Prediction model for compressive strength of rice husk ash blended sandcrete blocks using a machine learning models
Mabrouk, Ibrahim / Mahmoud, Mahmoud Hassan / Bushnaq, Muhammad Metwally	The process of rehabilitating reinforced concrete slabs using various materials such as steel bars, steel plates, textiles, and different types of geogrids
Ashwini, B. T. / Kumar, Y. M. Vijaya / Gowda, B. S. Keerthi / Kumar, D. T. Naveen	Prognostication of mechanical properties of banana and jute fiber reinforced concrete using ANN
Mokashi, Vishwajeet M. / Jadhav, H. S.	Progressive collapse analysis and seismic performance of irregular RC structures: a probabilistic approach
Singh, Hanumant Sharan / Shukla, Gaurav	Regression analysis of properties of GGBS based bacillus subtilis bacterial concrete
Banerjee, Rajiv / Gupta, Nakul / Singh, Prakash / Saxena, Kuldeep K. / Parashar, Arun Kumar	Seismic impact of re-entrant corners with varying angle on G + 15 story Y shaped irregular building
Gupta, Pranjal / Gupta, Chayan	Seismic performance evaluation of reinforced concrete flat slab buildings using ETABS
Mohan, A / Madhavi, T. Ch	A study on mechanical properties of inorganic binders used in textile reinforced concrete using artificial neural network
Misal, Mrunmyee A. / Manchalwar, Atulkumar A. / Nangare, P. B.	Vibration control of structure using inelastic tuned mass damper

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sur cette fiche
IssueID
28487
Publié(e) le:
28.06.2019
Modifié(e) le:
01.07.2019

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International Association for Bridge and Structural Engineering (IABSE)

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Asian Journal of Civil Engineering -

Articles dans ce numéro

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Asian Journal of Civil Engineering -

Articles dans ce numéro

Vous avez dépassé votre limite de téléchargement mensuelle ! Les abonné·es à Structurae Plus peuvent télécharger 30 images ou ensembles de données par mois. Les utilisateurs·rices de Structurae Pro sont limités à 50.

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