Causative factors of construction and demolition waste generation in Iraq Construction Industry

The construction industry has hurt the environment from the waste generated during construction activities. Thus, it calls for serious measures to determine the causative factors of construction waste generated. There are limited studies on factors causing construction, and demolition (C&D) waste generation, and these limited studies only focused on the quantification of construction waste. This study took the opportunity to identify the causative factors for the C&D waste generation and also to determine the risk level of each causal factor, and the most important minimization methods to avoiding generating waste. This study was carried out based on the quantitative approach. A total of 39 factors that causes construction waste generation that has been identified from the literature review were considered which were then clustered into 4 groups. Improved questionnaire surveys by 38 construction experts (consultants, contractors and clients) during the pilot study. The actual survey was conducted with a total of 380 questionnaires, received with a response rate of 83.3%. Data analysis was performed using SPSS software. Ranking analysis using the mean score approach found the five most significant causative factors which are poor site management, poor planning, lack of experience, rework and poor controlling. The result also indicated that the majority of the identified factors having a high-risk level, in addition, the better minimization method is environmental awareness. A structural model was developed based on the 4 groups of causative factors using the Partial Least Squared-Structural Equation Modelling (PLS-SEM) technique. It was found that the model fits due to the goodness of fit (GOF ≥ 0.36= 0.658, substantial). Based on the outcome of this study, 39 factors were relevant to the generation of construction and demolition waste in Iraq. These groups of factors should be avoided during construction works to reduce the waste generated. The findings of this study are helpful to authorities and stakeholders in formulating laws and regulations. Furthermore, it provides opportunities for future researchers to conduct additional research’s on the factors that contribute to construction waste generation

Metody inicializace vah pro neuronové sítě typu MLP

This paper describes the weights initialization methods for two-layer feedforward neural networks. The choice of method influences of a convergence and a minimal final value of cost function for a neural network training process. The neural networks application in different domain to be expected, that their users will be acquired the applicable neural network models. Hence it is important prune away all kinds of an uncertainties while the choice of neural network structure, the learning algorithm in context of other adjustable parameters as well as preparing of suitable learning and testing data set for the neural network learning.Příspěvek popisuje inicializační metody vah spojení pro dvouvrstvé dopředné neuronové sítě, jejichž volba má vliv na rychlost a minimální výslednou hodnotu účelové funkce při vlastním učení neuronových sítí. Aplikace neuronových sítí v různých oborech předpokládá, že jejich uživatelé získají takové modely neuronových sítí, které budou použitelné. Proto je důležité odstranit všechny možné nejasnosti při volbě typu a struktury neuronové sítě, metodě učení v souvislosti s dalšími stavitelnými parametry i sestavení vhodných vzorů pro učení a testování neuronové sítě