Neural Network-Ant Colony Optimization Model of Residential Building Project Cost: Exploratory Approach

Neural network and ant-colony are two important tools that could be used to provide solution in situation of multivariate environment that requires pareto optima solutions. In this study therefore, combination of neural network and ant colony method was used to generate an optimization cost model. Neural network is a conventional method currently being used in cost modeling, given its advantage over traditional regression method. It is based on this, that this study used the combination of neural network and regression method to model cost of residential building projects. One hundred and fifty (150) samples of residential building projects were selected at random and divided into two; one part is used in developing network algorithm for neural network and ant colony, while the second part is used for model validation. Neural network is used to generate which was divided into modules: the data optimization module, criteria selection with initializing and terminating modules. Regression analysis was carried out and model validated with Jackknife re-sampling technique and previously developed ant colony model (MOACO, MOTACO and MAWA). The co-linearity analysis indicates high level of tolerance and -0.0756 lowest variation prediction quotients to 0.8678 highest variation quotients. Also the Regression coefficient (R-square) value for determining the model fitness is 0.069 with standard error of 0.045. These results attests to the fitness of the model generated. The model is flexible in accommodating new data and variables, thus, it allows for continuous updating. Keywords: Expert system, Co-linearity, Informatics, Residential-Building

Survey datasets on women participation in green jobs in the construction industry

The unique qualities of women can make them bearers of solutions towards achieving sustainability and dealing with the dangers attributed to climate change. The attitudinal study utilized a questionnaire instrument to obtain perception of female construction professionals. By using a well-structured questionnaire, data was obtained on women participating in green jobs in the construction Industry. Descriptive statistics is performed on the collected data and presented in tables and mean scores (MS). In addition, inferential statistics of categorical regression was performed on the data to determine the level of influence (beta factor) the identified barriers had on the level of participation in green jobs. Barriers and the socio-economic benefits which can guide policies and actions on attracting, retaining and exploring the capabilities of women in green jobs can be obtained from the survey data when analyzed

Building Practice in the New Millennium: is Building Education Ready to Meet the Challenges

The study aimed at assessing the building prncticc in the new millennium and cvahwtcd the readiness of building education in meeting these challenges. The objectives of this research are to evaluate building education and practices in the ne·w millemlium .. identify the challenges building practices face in the ne·w nlillemlitml and evaluate the readiness of building education in meeting these challenges. Secondary and primary data were obtained. Data ·was obtained by the adnlinistration of questionnaires. and interviews of students studying Building Technology in Covenant University and construction practitioners. A sample size of 150 students comprising of students from the 5 levels of the progrmmne partook of the survey. Purposeful sampling technique was used and the data obtained was analyzed using a 5-point Likert scale. The factors affecting the readiness of building education in meeting the challenges of Building Prncticc in the New Millennium in varying degrees include Poor Educational Background, Poor curriculum. Poor Relationship Between Educational System and The Constmction Industry. Lack of Prospect To Take Risk. Insufficient Building Practice. Cormption., Financial Inadequacy and Economic Recession. It was also observed that that the education sector and public lack awareness of what building millennium entails and do not have the pre requites building education that can meet up with the rapidly evolving standards of the nilllennium. The study therefore concluded that the building education is not ready to f.1cc the challenges of the new millennium; it recommended that the curriculum should be assessed and restmctured to be able to meet up the requirements of the new nlillennium building constructio

Data on mixing and curing methods effects on the compressive strength of concrete

Curing, though important is sometimes underrated in concrete production. This dataset provided shows the effects of four (4) different methods of curing on two distinct mix ratios. The data provided in this article are for a study that was conducted on one hundred and sixty (160) cube samples of mix ratios 1:2:4 and 1:1.5:3 while employing four (4) different methods of curing. The data given in the article displays the finding of the study. The findings can aid in prediction and optimization of concrete behavior and compressive strength when any of the curing methods are utilized