Using random inquiry optimization method for provision of heat and cooling demand in hub systems for smart buildings

Jabarullah, Noor H.; Shabbir, Muhammad Salman; Abbas, Mazhar; Siddiqi, Ahmed Faisal; Berti, Stephen

doi:10.1016/j.scs.2019.101475

Cited by 29 publications

(15 citation statements)

References 24 publications

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“…AHP is one approach that can be implemented in selecting the requirement. Using the AHP method, we can set certain criteria for some requirements to choose the highest priority (Jabarullah et al, 2019). On this research, we choose 4 criteria that are cost, risk, difficulty, and stability.…”

Section: Discussionmentioning

confidence: 99%

Defining and Prioritizing Software Requirement Using gIBIS and AHP Method

Falahah¹

2019

ujeee

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Requirement engineering is an important process in a software development project. During the process there are two activities that are very significant that determine the success of the software development: requirement definition and requirement prioritization. Through this process we can set the scope of the software product and the limitations of product features for each released version. Defining and prioritizing requirements can be done using same approach. gIBIS (graphical Issue-Based Information System) is a proposed approach for the design rationale to describe the reasoning process for the solution that is chosen in order to answer a problem or issue. The graphical representation of the reasoning process using gIBIS can be supported by tools such as Compendium. This paper proposes the implementation of the gIBIS approach in defining software requirements by assigning a score for each alternative and selecting the highest score as a solution. The approach is combined with AHP (Analytical Hierarchical Process) method to set the priority and as the result we can determine the software requirements and also rank the requirements based on its priority. The criteria used in setting the priority include cost, risk, difficulty and stability. The proposed approach (combining of gIBIS and AHP) is demonstrated with a case study of prioritizing requirements for a website development of "IndoSoccerSchool". The result show that the proposed approach can help us generate a list of requirements and give them a score based on priority and the list can give a reference for developing the software based on credible priorities and then manage the software release.

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Section: Discussionmentioning

confidence: 99%

Defining and Prioritizing Software Requirement Using gIBIS and AHP Method

Falahah¹

2019

ujeee

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“…A study revealed that providing valuable resources required to build capabilities that enhance a firm's performance is the way to ensure a sustainable advantage [93]. The existing literature between MCS and business strategies is limited, which provides substantial evidence that additional studies are needed [87,94]. The research confirmation on the association between MCS and the business strategies are fragmented, Sustainability 2019, 11, 4705 7 of 20 and sometimes conflict as a business strategy because it is operationalized differently as well as calculated in various ways in contingency studies [25,95].…”

Section: Business Strategiesmentioning

confidence: 99%

The Mediating Role of Business Strategies between Management Control Systems Package and Firms Stability: Evidence from SMEs in Malaysia

et al. 2019

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The aim of the current study was to ascertain the influence of a management control systems (MCS) package on a firm's sustainability with the help of mediating variables such as differentiation and cost leadership strategy in Malaysian small and medium enterprises (SMEs). Data were collected from managers working in Malaysian SMEs. A total of 384 questionnaires was finally used for analysis using SmartPLS 3.8.2. Area cluster sampling was used for data collection, and seven out of sixteen clusters were selected randomly. These included Selangor, Johor, Kuala Lumpur, Sabah, Penang, Sarawak, and Perak because these seven states cover 73.9% of total SMEs. Structural equation modeling (SEM) was used to test the hypotheses. Confirmatory factor analysis (CFA) was also used to examine the reliability and validity, and structural model assessment was used to test the relationship between variables. Findings revealed that an MCS package had a positive influence on a firm's sustainability, cost leadership, and differentiation strategy. Moreover, cost leadership and differentiation strategy have a significant and positive influence on a firm's sustainability. In addition, cost leadership strategies and differentiation strategies significantly mediate between the MCS package and a firm's sustainability. This research assesses the influence of the MCS package through cost leadership and differentiation strategy on a firm's sustainability of Malaysian SMEs. It helps top management to focus on the MCS package and business strategies in attaining a firm's long-term sustainability. Finally, research recommendations discuss that the present study helps future researchers and academicians.

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“…In this case, N is the number of variables identified as the input (i.e., 8 explanatory variables identified from the literature above). The hidden layer is captured based on the sigmoid transfer function for each hidden node which then allows the network to generate the output and is thus expressed as follows [73]:…”

Section: Artificial Neural Networkann Modelmentioning

confidence: 99%

Artificial Neural Network to Model Managerial Timing Decision: Non-linear Evidence of Deviation from Target Leverage

Hussain¹,

Kamarudin²,

Thaker³

et al. 2019

IJCIS

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The current study highlights the utilization of a non-linear model to analyze an important decision-making process in the study of corporate finance where managers are deciding on the capital structure of a firm. This study compares the results from based on the unbalanced panel data multiple regression for firm fixed effects relative to the artificial neural networks, i.e., ANN, with known determinants of capital structure as control variables for a sample of UK firms respectively. Results of the study show that firms are timing away from target levels which challenges the current findings in the literature. The ANN model achieves a better fit based on the root of mean-squared error (RMSE) values which provides a more accurate forecast. Thus, the nature of balancing between cost of being off-target versus benefits gained from timing the equity market is non-linear and which is captured by ANN. Implications from the study allow market players to understand the process of achieving optimal capital structure to maximize firm value and thus benefit all stakeholders.

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Using random inquiry optimization method for provision of heat and cooling demand in hub systems for smart buildings

Cited by 29 publications

References 24 publications

Defining and Prioritizing Software Requirement Using gIBIS and AHP Method

Defining and Prioritizing Software Requirement Using gIBIS and AHP Method

The Mediating Role of Business Strategies between Management Control Systems Package and Firms Stability: Evidence from SMEs in Malaysia

Artificial Neural Network to Model Managerial Timing Decision: Non-linear Evidence of Deviation from Target Leverage

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