Fuzzy Logic Based Support Vector Regression (SVR) Model for Software Cost Estimation Using Machine Learning

Upreti, Kamal; Singh, Umesh Kumar; Jain, Rituraj; Kaur, Karamjeet; Sharma, Arvind Kumar

doi:10.1007/978-981-16-5987-4_90

Cited by 14 publications

(4 citation statements)

References 7 publications

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“…It also contributes to the formation of high-strength GPC [28,29]. All alternative materials used in building construction components have a lower energy level than conventional building materials [28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46].…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis of Geopolymer Concrete: A Sustainable and Economic Concrete Using the Cost Estimation Model

Verma

Upreti²,

Vats

et al. 2022

Advances in Materials Science and Engineering

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Geopolymer concrete is sustainable, economical, eco-friendly, durable, and high-strength concrete. Geopolymer is a name for the bonding that occurs during the binding of materials in alkaline conditions. Due to the presence of high silica and alumina content, pozzolanic materials could be used as binding materials in the GPC. This research aims to check the sustainability and cost analysis of both GPC and conventional concrete with their physical, chemical, and mechanical properties. The experimental investigation analyzes both GPC and OPC concrete’s physical, chemical, and mechanical properties for the M30 mix design and analyzes the concrete’s cost and sustainability. The experimental investigation shows that the setting time, density, and drying shrinkage of conventional concrete are higher than the GPC. The compressive strength of the GPC and OPC concretes both showed similar trends at the 28-day strength, but the initial three-day strength of the GPC concrete was much higher than the OPC concrete. The splitting tensile strength and flexural strength of the GPC specimens are slightly higher than the OPC concrete mix specimens. The OPC concrete’s elastic modulus is slightly higher than the GPC mix design, whereas the Poisson’s ratio of the OPC concrete is slightly lower than the GPC specimens. The GPC specimens have higher thermal stability up to 800°C. The GPC utilizes industrial solid waste like fly ash and slag as a binding material and is activated by an alkaline solution containing NaOH and Na2SiO3 in the design mix. Therefore, the GPC has less embodied energy compared to the OPC concrete. The cost of the GPC at a bulk level reduced the cost of up to 40% of the OPC concrete.

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Section: Introductionmentioning

confidence: 99%

Experimental Analysis of Geopolymer Concrete: A Sustainable and Economic Concrete Using the Cost Estimation Model

Verma

Upreti²,

Vats

et al. 2022

Advances in Materials Science and Engineering

Self Cite

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“…The bit length for secure RSA use has risen over the years, putting a larger processing burden on systems that use this algorithm. The usage of this algorithm has overwhelmed the proper functioning, especially for the e-commerce websites that are prone to deal with voluminous and secured transactions [17,26]. For this reason, a comparative study between RSA and ECC was done, which resulted to be beneficial for ECC, although the level of security was equally the same, but the data size that was considered was of smaller bit size, due to which the processing time was comparatively less than RSA [5,28].…”

Section: Ellipic Curve Cryptographymentioning

confidence: 99%

Analysis of Elliptic Curve Cryptography & RSA

Khan,

Upreti,

Alam

et al. 2023

JICTS

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In today’s digital world, the Internet is an essential component of communication networks. It provides a platform for quickly exchanging information among communicating parties. There is a risk of unauthorized persons gaining access to our sensitive information while it is being transmitted. Cryptography is one of the most effective and efficient strategies for protecting our data and it are utilized all around the world. The efficiency of a cryptography algorithm is determined by a number of parameters, one of which is the length of the key. For cryptography, key (public/private) is an essential part. To provide robust security, RSA takes larger key size. If we use larger key size, the processing performance will be slowed. As a result, processing speed will decrease and memory consumption will increase. Due to this, cryptographic algorithms with smaller key size and higher security are becoming more popular. Out of the cryptographic algorithms, Elliptic Curve Cryptography (ECC) provides equivalent level of safety which RSA provides, but it takes smaller key size. On the basis of key size, our work focused on, studied, and compared the efficacy in terms of security among the well-known public key cryptography algorithms, namely ECC (Elliptic Curve Cryptography) and RSA (Rivets Shamir Adelman).

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“…e level of knowledge is different among estimators, which can affect the accuracy of the cost estimation process [13]. Many studies have used statistical and artificial intelligence techniques to prevent these problems and accurately estimate construction costs [13,32,33]. Several studies performed the regression method as a traditional technique for cost estimation [34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

Developing an Integrative Data Intelligence Model for Construction Cost Estimation

et al. 2022

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Construction cost estimation is one of the essential processes in construction management. Project cost is a complex engineering problem due to various factors affecting the construction industry. Accurate cost estimation is important in construction management and significantly impacts project performance. Artificial intelligence (AI) models have been effectively implemented in construction management studies in recent years owing to their capability to deal with complex problems. In this research, extreme gradient boosting is developed as an advanced input selector algorithm and coupled with three AI models, including random forest (RF), artificial neural network (ANN), and support vector machine (SVM) for cost estimation. Datasets were gathered based on a survey conducted on 90 building projects in Iraq. Statistical indicators and graphical methods were used to evaluate the developed models. Several input predictors were used, and XGBoost highlighted inflation as the most crucial parameter. The results indicated that the best prediction was attained by XGBoost-RF using six input parameters, with r-squared and the mean absolute percentage error equal to 0.87 and 0.25, respectively. The comparison results revealed that all AI models showed good prediction performance when applied to datasets affected by more than two parameters. The outcomes of this research revealed an optimistic strategy that can help decision makers select the influencing parameters in the early phases of project management. Also, developing a prediction model with high precision results can assist the project’s estimators in decreasing the errors in the cost estimation process.

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Fuzzy Logic Based Support Vector Regression (SVR) Model for Software Cost Estimation Using Machine Learning

Cited by 14 publications

References 7 publications

Experimental Analysis of Geopolymer Concrete: A Sustainable and Economic Concrete Using the Cost Estimation Model

Experimental Analysis of Geopolymer Concrete: A Sustainable and Economic Concrete Using the Cost Estimation Model

Analysis of Elliptic Curve Cryptography & RSA

Developing an Integrative Data Intelligence Model for Construction Cost Estimation

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