3,182 research outputs found
Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
The declining of air quality mostly affects the elderly, children, people with asthma,
as well as a restriction on outdoor activities. Therefore, there is an importance to
provide a statistical modelling to forecast the future values of surface layer ozone (O3)
concentration. The objectives of this study are to obtain the best multivariate time
series (MTS) model and develop an online air quality forecasting system for O3
concentration in Malaysia. The implementations of MTS model improve the recent
statistical model on air quality for short-term prediction. Ten air quality monitoring
stations situated at four (4) different types of location were selected in this study. The
first type is industrial represent by Pasir Gudang, Perai, and Nilai, second type is urban
represent by Kuala Terengganu, Kota Bharu, and Alor Setar. The third is suburban
located in Banting, Kangar, and Tanjung Malim, also the only background station at
Jerantut. The hourly record data from 2010 to 2017 were used to assess the
characteristics and behaviour of O3 concentration. Meanwhile, the monthly record data
of O3, particulate matter (PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2),
carbon monoxide (CO), temperature (T), wind speed (WS), and relative humidity (RH)
were used to examine the best MTS models. Three methods of MTS namely vector
autoregressive (VAR), vector moving average (VMA), and vector autoregressive
moving average (VARMA), has been applied in this study. Based on the performance
error, the most appropriate MTS model located in Pasir Gudang, Kota Bharu and
Kangar is VAR(1), Kuala Terengganu and Alor Setar for VAR(2), Perai and Nilai for
VAR(3), Tanjung Malim for VAR(4) and Banting for VAR(5). Only Jerantut obtained
the VMA(2) as the best model. The lowest root mean square error (RMSE) and
normalized absolute error is 0.0053 and <0.0001 which is for MTS model in Perai and
Kuala Terengganu, respectively. Meanwhile, for mean absolute error (MAE), the
lowest is in Banting and Jerantut at 0.0013. The online air quality forecasting system
for O3 was successfully developed based on the best MTS models to represent each
monitoring station
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
Mechanical properties of the concrete containing porcelain waste as sand
The demand of concrete have been increases on a daily bases which consume a lot of natural resource such as sand and gravel, there is an immediate need for finding suitable alternative which can be used to replace sand partially with another materials with high propor-tion . Ceramic waste is one of the strongest research areas that include the activity of replacement in all the sides of construction materi-als. This research aims to improve the performance of concrete using ceramic waste, and demonstrate the performance of mechanical properties to the concrete with partial replacement of sand by using waste porcelain. For these, we analyzed the mechanical properties of the concrete such as compressive strength, split tensile and flexural strength, the specimen were measured based on 10% ,20% ,30% ,40%, and 50% weight ratio of replace sand with waste porcelain at different time under water for 7 days , 28 days , 60 days . The optimum consideration were given to mechanical properties of the concrete, at different amount of ceramic waste as sand
Cuckoo Search Inspired Hybridization of the Nelder-Mead Simplex Algorithm Applied to Optimization of Photovoltaic Cells
A new hybridization of the Cuckoo Search (CS) is developed and applied to
optimize multi-cell solar systems; namely multi-junction and split spectrum
cells. The new approach consists of combining the CS with the Nelder-Mead
method. More precisely, instead of using single solutions as nests for the CS,
we use the concept of a simplex which is used in the Nelder-Mead algorithm.
This makes it possible to use the flip operation introduces in the Nelder-Mead
algorithm instead of the Levy flight which is a standard part of the CS. In
this way, the hybridized algorithm becomes more robust and less sensitive to
parameter tuning which exists in CS. The goal of our work was to optimize the
performance of multi-cell solar systems. Although the underlying problem
consists of the minimization of a function of a relatively small number of
parameters, the difficulty comes from the fact that the evaluation of the
function is complex and only a small number of evaluations is possible. In our
test, we show that the new method has a better performance when compared to
similar but more compex hybridizations of Nelder-Mead algorithm using genetic
algorithms or particle swarm optimization on standard benchmark functions.
Finally, we show that the new method outperforms some standard meta-heuristics
for the problem of interest
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