2020
DOI: 10.3390/app10207159
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Constraints Hindering the Development of High-Rise Modular Buildings

Abstract: Off-site construction has been increasingly employed due to its advantages, for instance, improved quality control, reduced skills labour, faster construction time, decreased material wastage and safe working environment. As the most cutting-edge off-site construction, modular buildings have been utilised for residential building, student accommodation, and hotel projects. However, because of existing and underlying constraints, the adoption of modular buildings is still relatively low. To reveal factors hinde… Show more

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Cited by 65 publications
(26 citation statements)
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References 74 publications
(77 reference statements)
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“…The construction industry has been conservative in adopting new technologies; in fact, it does not adopt them until their additional value has been demonstrated [27]. Therefore, the proportion of modular construction projects cannot increase until the negative perceptions about them disappear.…”
Section: Efforts To Promote Modular Construction Projectsmentioning
confidence: 99%
“…The construction industry has been conservative in adopting new technologies; in fact, it does not adopt them until their additional value has been demonstrated [27]. Therefore, the proportion of modular construction projects cannot increase until the negative perceptions about them disappear.…”
Section: Efforts To Promote Modular Construction Projectsmentioning
confidence: 99%
“…There are many problems that their feature space is more complex than the assessed benchmark spaces [107][108][109][110][111]. Despite benchmark cases, engineering problems always involve some variables that are constrained [28,[112][113][114][115]. For testing and benchmarking the proposed algorithm, some popular and perplexing engineering functions are common in the literature.…”
Section: Engineering Problemsmentioning
confidence: 99%
“…As well as this, other difficulties such as the non-linearity of the problem have driven many scholars to improve the flexibility of intelligent models. As discussed by many scholars, along with well-known models (e.g., decision-making [6][7][8][9]), the artificial intelligence techniques have provided a high capability in the estimation of non-linear and intricate parameters [10][11][12]. Plenty of scientific efforts (e.g., concerning environmental subjects [13][14][15][16][17][18][19][20][21][22][23], gas consumption modeling [24,25], sustainable developments [26], pan evaporation and soil precipitation simulation [26][27][28][29][30][31], energy-related estimations [32][33][34][35][36][37][38][39], water supply assessment [16,[40][41][42][43][44][45][46][47][48][49], computer v...…”
Section: Introductionmentioning
confidence: 99%
“…Different structures (and consequently diverse types) of ANNs have been designed for specific objectives (e.g., multilayer perceptron (MLP) [77][78][79]). Going into deep processors such as ANN, a so-called method "deep learning" emerges, which has successfully modeled various phenomena and parameters [8,[80][81][82]. Diagnostic problem and medical sciences, for instance, are two subjects which have been nicely solved by extreme machine learning approaches [83][84][85][86].…”
Section: Introductionmentioning
confidence: 99%