A formal evaluation of KNN and decision tree algorithms for waste generation prediction in residential projects: a comparative approach (English)
- New search for: Gulghane, Akshay
- New search for: Sharma, R. L.
- New search for: Borkar, Prashant
- New search for: Gulghane, Akshay
- New search for: Sharma, R. L.
- New search for: Borkar, Prashant
In:
Asian Journal of Civil Engineering
: Building and Housing
;
25
, 1
;
265-280
;
2024
- Article (Journal) / Electronic Resource
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Title:A formal evaluation of KNN and decision tree algorithms for waste generation prediction in residential projects: a comparative approach
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Additional title:Asian J Civ Eng
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Contributors:
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Published in:Asian Journal of Civil Engineering : Building and Housing ; 25, 1 ; 265-280
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Publisher:
- New search for: Springer International Publishing
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Place of publication:Cham
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Publication date:2024-01-01
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Size:16 pages
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ISSN:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents – Volume 25, Issue 1
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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Seismic performance evaluation of a tall building with dual lateral system consisting of moment frames and tuned mass dampersMatinrad, Pezhman / Banazadeh, Mehdi / Taslimi, Arsam et al. | 2024
- 19
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Numerical modeling to predict the impact of granular glass replacement on mechanical properties of mortarAhmad, Soran Abdrahman / Rafiq, Serwan Khwrshid et al. | 2024
- 39
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A machine learning approach for health monitoring of a steel frame structure using statistical features of vibration dataNaresh, Maloth / Kumar, Vimal / Pal, Joy et al. | 2024
- 51
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Fast prediction of the compressive strength of high-performance concrete through a k-nearest neighbor approachPhan, Tan-Duy et al. | 2024
- 67
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A mathematical model to predict the porosity and compressive strength of pervious concrete based on the aggregate size, aggregate-to-cement ratio and compaction effortWijekoon, Sathushka Heshan / Shajeefpiranath, Thirugnasivam / Subramaniam, Daniel Niruban / Sathiparan, Navaratnarajah et al. | 2024
- 81
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The effects of selection and scaling procedures of earthquake records on the seismic response dispersion of structures and recommendations toward seismic upgrading of codesMansouri, Saman / Kontoni, Denise-Penelope N. / Pouraminian, Majid et al. | 2024
- 97
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Numerical investigation of various techniques for strengthening the external RC frame connectionAbou Elezz, A. E. Y. / Mohamed, R. A. S. / Abd Elhameed, R. M. M. et al. | 2024
- 115
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Numerical analysis of steel beam–column connection under cyclic loading with dog bone type fusesVesmawala, Gaurang / Mehta, Rudradatta et al. | 2024
- 123
-
Numerical investigation on two-way voided slab using ABAQUS with replacement of conventional steel with GFRP reinforcement barsJain, Nikita / Hussain, Asif et al. | 2024
- 129
-
Modeling vibration and crack behavior of reinforced concrete beams: developing artificial neural network predictive modelsKhateeb, Ahmed H. / Abdulwahed, Larah R. / Mohammed, Aymen R. et al. | 2024
- 141
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Explainable XGBoost machine learning model for prediction of ultimate load and free end slip of GFRP rod glued-in timber joints through a pull-out test under various harsh environmental conditionsTajik, Nima / Mahmoudian, Alireza / Mohammadzadeh Taleshi, Mostafa / Yekrangnia, Mohammad et al. | 2024
- 159
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Predicting and forecasting building energy performance using RSM and ANNPatil, Satish Ramesh / Sinha, Manish Kumar / Deshmukh, Mrunalini Amol / Thenmozhi, S. / Sujatha, A. et al. | 2024
- 167
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Old masonary tower analysis visual inspection, NDT, and macro-modelingKumar, Ambareesh / Pallav, Kumar et al. | 2024
- 183
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Application of soft computing in predicting the compressive strength of self-compacted concrete containing recyclable aggregateAlbostami, Asad S. / Al-Hamd, Rwayda Kh. S. / Alzabeebee, Saif / Minto, Andrew / Keawsawasvong, Suraparb et al. | 2024
- 197
-
Enhancing prediction accuracy of workability and compressive strength of high-performance concrete through extended dataset and improved machine learning modelsTipu, Rupesh Kumar / Suman / Batra, Vandna et al. | 2024
- 219
-
Using explainable machine learning to predict compressive strength of blended concrete: a data-driven metaheuristic approachKashifi, Mohammad Tamim / Salami, Babatunde Abiodun / Rahman, Syed Masiur / Alimi, Wasiu et al. | 2024
- 237
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Design of simply supported composite slabs of steel and concrete via metaheuristic optimization algorithmTeixeira, Mariana Oliveira / Alves, Élcio Cassimiro / de Oliveira Valle, Janaina Pena Soares / Calenzani, Adenilcia Fernanda Grobério et al. | 2024
- 253
-
Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithmsAl-Rawashdeh, Mohammad / Al Nawaiseh, Moh’d / Yousef, Isam / Bisharah, Majdi / Alkhadrawi, Sajeda / Al-Bdour, Hamza et al. | 2024
- 265
-
A formal evaluation of KNN and decision tree algorithms for waste generation prediction in residential projects: a comparative approachGulghane, Akshay / Sharma, R. L. / Borkar, Prashant et al. | 2024
- 281
-
NDT-based condition assessment and repair technique for an RCC building with wind turbines mounted on the rooftop: a case studyAravalli, Naresh / Sale, Vikas / Lute, Venkat et al. | 2024
- 295
-
Proposed shear strength structures, experiment, simulation, and analytic model of reinforced concrete flat slab and concrete-filled steel tube columnAhmed, Reem Hatem / Elaiwi, Sahar / Ameen, Shelan Hameed et al. | 2024
- 303
-
Structural health monitoring of ASCE benchmark building using machine learning algorithmsPalsara, Chandesh / Kumar, Vimal / Pal, Joy / Naresh, M. et al. | 2024
- 317
-
Mechanical and durability analysis of geopolymer concrete incorporating bauxite residue, phosphogypsum, and ground granulated blast slagPratap, Bheem / Mondal, Somenath / Rao, B. Hanumantha et al. | 2024
- 327
-
Prediction of high-performance concrete compressive strength using deep learning techniquesIslam, Naimul / Kashem, Abul / Das, Pobithra / Ali, Md. Nimar / Paul, Sourov et al. | 2024
- 343
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ANN prediction model to improve employees’ thermal satisfaction in tropical green office buildingsAbeyrathna, Wasudha Prabodhani / Ariyarathna, Isuri Shanika / Halwatura, R. U. / Arooz, F. R. / Perera, A. S. / Kaklauskas, Arturas et al. | 2024
- 359
-
Comparative study on the behaviour of castellated beams provided with hexagonal, circular, and diamond-shaped web openingsPatil, Sourabh S. / Kumbhar, Popat D. et al. | 2024
- 371
-
The influence of interactions between two high-rise buildings on the wind-induced momentYadav, Himanshu / Roy, Amrit Kumar / Kumar, Anoop et al. | 2024
- 385
-
A hybrid Modified Artificial Bee Colony and extended Kalman filter algorithm for structural system identificationMalathy, R. B. et al. | 2024
- 397
-
Nonlinear behaviour of a reinforced concrete building subjected to blast load and optimisation using a meta-heuristic algorithmYadhav, Adinath / Gosavi, Shubham / Kulkarni, Mrudula et al. | 2024
- 413
-
Parametric investigation of tuned mass damper on metallic buildings response subjected to far-field and near-fault ground motionsRas, Abdelouahab et al. | 2024
- 427
-
Finite element analysis of interlocking masonry subjected to static loadingRasul, Suhaib / Kumar, Vimal et al. | 2024
- 443
-
Sand fineness modulus prediction in construction sector using convolutional neural networkFahad, AL / Nayem, Naymul Hasan / Hossain, Md. Nashib / Rabbani, Md. Liton / Opu, Raihan Khan / Al Shuaeb, S M Abdullah et al. | 2024
- 451
-
Comparative study on the behaviour of conventional and pre-engineered buildings provided with different types of bracingBharmal, Pravin P. / Kumbhar, Popat D. / Gumaste, Krishnakedar S. et al. | 2024
- 461
-
Numerical study of concentrically braced frames with the replaceable reduced section under cyclic loadingRamezantitkanloo, Amin / Kafi, Mohammad Ali / Kachooee, Ali et al. | 2024
- 477
-
FE modeling for ultimate behavior predictions of RC beamPandimani / Rao, Yeduvaka Damodara / Krishna, Ijada Gopala et al. | 2024
- 495
-
Effect of aggregate size, aggregate to cement ratio and compaction energy on ultrasonic pulse velocity of pervious concrete: prediction by an analytical model and machine learning techniquesSathiparan, Navaratnarajah / Jeyananthan, Pratheeba / Subramaniam, Daniel Niruban et al. | 2024
- 511
-
Artificial neural network and machine learning models for predicting the lateral cyclic response of post-tensioned base rocking steel bridge piersNabizadeh, Elham / Parghi, Anant et al. | 2024
- 525
-
Performance of different machine learning techniques in predicting the flexural capacity of concrete beams reinforced with FRP rodsNgamkhanong, Chayut / Alzabeebee, Saif / Keawsawasvong, Suraparb / Thongchom, Chanachai et al. | 2024
- 537
-
Numerical investigation of reinforced concrete beams under impact loadingDhiman, Prince / Kumar, Vimal et al. | 2024
- 555
-
Seismic performance enhancement of RC framed structures through retrofitting and strengthening: an experimental and numerical studyWahab, Abdul Ghafar / Zhong, Tao / Wei, Fangfang / Hakimi, Nadimullah / Ahiwale, Dhiraj D. et al. | 2024
- 575
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Towards sustainable reinforced concrete beams: multi-objective optimization for cost, CO2 emission, and crack preventiondos Santos, Nathanael Risson / Alves, Elcio Cassimiro / Kripka, Moacir et al. | 2024
- 583
-
Prediction of the compressive strength of normal concrete using ensemble machine learning approachSapkota, Sanjog Chhetri / Saha, Prasenjit / Das, Sourav / Meesaraganda, L. V. Prasad et al. | 2024
- 597
-
Prediction of compressive strength of bauxite residue-based geopolymer mortar as pavement composite materials: an integrated ANN and RSM approachPratap, Bheem / Mondal, Somenath / Rao, Bendadi Hanumantha et al. | 2024
- 609
-
Insight into the microstructural properties of bio-engineered concrete matrices and analysis by scanning electron microscopyRahman, Md. Asifur / Zawad, Md Fahad Shahriar / Priyom, Sudipto Nath / Islam, Md. Moinul et al. | 2024
- 623
-
The influence of fines on the hydro-mechanical behavior of sand for sustainable compacted liner and sub-base construction applicationsOnyelowe, Kennedy C. / Ebid, Ahmed M. / Hanandeh, Shadi / Moghal, Arif Ali Baig / Onuoha, Ifeanyi C. / Obianyo, Ifeyinwa I. / Stephen, Liberty U. / Ubachukwu, Obiekwe A. et al. | 2024
- 637
-
Enhancing chloride concentration prediction in marine concrete using conjugate gradient-optimized backpropagation neural networkTipu, Rupesh Kumar / Panchal, V. R. / Pandya, K. S. et al. | 2024
- 657
-
Assessment of the effects of infill walls’ layout in plan and/or elevation on the seismic performance of 3D reinforced concrete structuresGuettala, Salah / Abdesselam, Issam / Chebili, Rachid / Guettala, Salim et al. | 2024
- 675
-
Application of wavelet neural network for dynamic analysis of moment resisting framesJoshi, Shardul G. / Kwatra, Naveen et al. | 2024
- 685
-
Predicting compressive strength of concrete with fly ash and admixture using XGBoost: a comparative study of machine learning algorithmsGogineni, Abhilash / Panday, Indra Kumar / Kumar, Pramod / Paswan, Rajesh Kr. et al. | 2024
- 699
-
Predictive modelling of concrete compressive strength incorporating GGBS and alkali using a machine-learning approachGogineni, Abhilash / Panday, Indra Kumar / Kumar, Pramod / Paswan, Rajesh kr. et al. | 2024
- 711
-
Soft computing techniques to predict the electrical resistivity of pervious concreteSubramaniam, Daniel Niruban / Jeyananthan, Pratheeba / Sathiparan, Navaratnarajah et al. | 2024
- 723
-
Feature engineering for predicting compressive strength of high-strength concrete with machine learning modelsKumar, Pramod / Pratap, Bheem et al. | 2024
- 737
-
Exploring internal factors affecting construction labor productivity in Mumbai: a study using RII and fuzzy logicChaudhari, Rahul S. / Bhangale, Pankaj P. et al. | 2024
- 747
-
Residual strength index prediction of circular concrete-filled steel tubular columns through advanced machine learning methodsNarang, Aishwarya / Kumar, Ravi / Dhiman, Amit et al. | 2024
- 761
-
Effect of torsion on unequal single steel angle purlin sections under biaxial moments by Abaqus analysisHosin, Nasim / Moharana, Narayan Chandra et al. | 2024
- 773
-
Mathematical modeling techniques to predict the compressive strength of pervious concrete modified with waste glass powdersAhmad, Soran Abdrahman / Rafiq, Serwan Khwrshid / Hilmi, Hozan Dlshad M. / Ahmed, Hemn Unis et al. | 2024
- 787
-
Predicting strength of concrete containing waste foundry sand and glass waste using artificial neural networkSingh, Aditya Pratap / Sharma, Abhishek et al. | 2024
- 805
-
A novel non-destructive technique-based automated classification of construction material using machine learningDhingra, Nitika / Saluja, Nitin et al. | 2024
- 811
-
Optimization and prediction of mechanical properties of high-performance concrete with steel slag replacement as coarse aggregate: an experimental study using RSM and ANNSaravan, R. Arvind / Annadurai, R. et al. | 2024
- 827
-
One-dimensional convolutional neural network for damage detection of structures using time series dataTran, Viet-Linh / Vo, Trong-Cuong / Nguyen, Thi-Quynh et al. | 2024
- 861
-
The influence of fly ash and blast furnace slag on the compressive strength of high-performance concrete (HPC) for sustainable structuresOnyelowe, Kennedy C. / Ebid, Ahmed M. et al. | 2024
- 883
-
Efficient hybrid machine learning model for calculating load-bearing capacity of driven pilesNguyen, Trong-Ha / Nguyen, Kieu-Vinh Thi / Ho, Viet-Chuong / Nguyen, Duy-Duan et al. | 2024
- 895
-
Bond strength of fly ash and silica fume blended concrete mixesPadavala, Siva Shanmukha Anjaneya Babu / Kode, Venkata Ramesh / Dey, Subhashish et al. | 2024
- 911
-
Machine learning approach to study the mechanical properties of recycled aggregate concrete using copper slag at elevated temperatureSahu, Anasuya / Kumar, Sanjay / Srivastava, A. K. L. / Pratap, Bheem et al. | 2024
- 923
-
A new technique based on the gorilla troop optimization coupled with artificial neural network for predicting the compressive strength of ultrahigh performance concretePrakash, Shubhum / Kumar, Sanjay / Rai, Baboo et al. | 2024
- 939
-
Comparative study on behaviour of castellated beams with diamond- and hexagonal-shaped openings using CFRP stiffenersMali, Suyash S. / Kumbhar, Popat D. et al. | 2024
- 953
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Impact of the position and quantity of shear walls in buildings on the seismic performanceKhelaifia, Akram / Chebili, Rachid / Zine, Ali et al. | 2024
- 965
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Machine learning optimization and prediction of waste glass used as partial replacement of coarse aggregate in concreteMahajan, K. A. / Priyatham, BPRVS / Dhariwal, Saraswati Chand / Jose, J. Prakash Arul / Rao, G. Mallikarjuna / Nakkeeran, G. / Kumar, G. Prem et al. | 2024
- 977
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Compressive strength prediction of PET fiber-reinforced concrete using Dolphin echolocation optimized decision tree-based machine learning algorithmsParhi, Suraj Kumar / Patro, Sanjaya Kumar et al. | 2024
- 997
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GRG-optimized response surface powered prediction of concrete mix design chart for the optimization of concrete compressive strength based on industrial waste precursor effectOnyelowe, Kennedy C. / Ebid, Ahmed M. / Ghadikolaee, Mehrdad Razzaghian et al. | 2024
- 1007
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An integrated evaluation of waste materials containing recycled asphalt fine aggregates using central composite designRout, M. K. Diptikanta / Shubham, Kumar / Biswas, Sabyasachi / Sinha, Abdhesh Kumar et al. | 2024
- 1027
-
Advanced machine learning prediction of the unconfined compressive strength of geopolymer cement reconstituted granular sand for road and liner construction applicationsOnyelowe, Kennedy C. / Ebid, Ahmed M. / Hanandeh, Shadi et al. | 2024
- 1043
-
A comprehensive study of viscous damper configurations and vertical damping coefficient distributions for enhanced performance in reinforced concrete structuresParajuli, Samvid / Pokhrel, Priyanshu / Suwal, Rajan et al. | 2024
- 1061
-
Advancements and challenges in the application of artificial intelligence in civil engineering: a comprehensive reviewHarle, Shrikant M. et al. | 2024
- 1079
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CrackSpot: deep learning for automated detection of structural cracks in concrete infrastructureShashidhar, R. / Manjunath, D. / Shanmukha, S. M. et al. | 2024
- 1091
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Alkali–silica reaction expansion prediction in concrete using hybrid metaheuristic optimized machine learning algorithmsParhi, Suraj Kumar / Panigrahi, Saubhagya Kumar et al. | 2024
- 1115
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Analytical study on seismic strengthening of reinforced concrete frame equipped with steel damping system with shear mechanism fuseFoyouzati, Amin et al. | 2024
- 1129
-
Correction: Infrastructure damage assessment via machine learning approaches: a systematic reviewAbedi, Mohammadmahdi / Shayanfar, Javad / Al-Jabri, Khalifa et al. | 2024
- 1131
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Correction: Prediction of high-performance concrete compressive strength using deep learning techniquesIslam, Naimul / Kashem, Abul / Das, Pobithra / Ali, Md. Nimar / Paul, Sourov et al. | 2024
- 1133
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Correction: Structural grade development for round bamboo: A ReviewShikur, Beharu D. / Zerayohannes, Girma / Gebre, Abrham et al. | 2024