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The purpose of this paper is to propose a novel data-driven approach for predicting energy performance of buildings that can address the scarcity of quality data, and consider the dynamic nature of building systems.

This paper proposes a reinforcing machine learning (ML) approach based on transfer learning (TL) to address these challenges. The proposed approach dynamically incorporates the data captured by the building management systems into the model to improve its accuracy.

It was shown that the proposed approach could improve the accuracy of the energy performance prediction compared to the conventional TL (non-reinforcing) approach by 19 percentage points in mean absolute percentage error.

The case study results confirm the practicality of the proposed approach and show that it outperforms the standard ML approach (with no transferred knowledge) when little data is available.

This approach contributes to the body of knowledge by addressing the limited data availability in the building sector using TL; and accounting for the dynamics of buildings’ energy performance by the reinforcing architecture. The proposed approach is implemented in a case study project based in London, UK.

Circular economy (CE) disclosure is becoming urgent for firms, but an accepted and recognized approach to address it is still missing, especially at small and medium enterprises (SMEs) level. This study aims to contribute to this issue by exploring the potential of the adoption of Global Reporting Initiative (GRI) Standards as a standardized approach for CE disclosure. The paper proposes a framework that identifies the existence of specific relationships between the topics included in GRI 300 Standards and CE strategies, which can be considered as managerial guidelines for CE strategy disclosure by companies.

The paper uses an explorative research methodology based on the content analysis of secondary data taken from the sustainability reports of the SMEs listed in STAR segment of Borsa Italiana.

The analysis shows that GRI Standards are currently adopted to disclose the CE strategies by Italian SMEs across different economic sectors including construction, food, automotive, retail, personal and household goods, industrial goods and services, electronics, media and technology. In particular, GRI 301 is used for the disclosure about Recycling, Reuse, Reverse logistics, Industrial Symbiosis, Eco-Design, Product as a Service and Refurbishing/Reconditioning/Remanufacturing. GRI 302 is suited to disclose CE strategies about Eco-Design, Renewable Energy and Industrial Symbiosis. GRI 303 can be useful to disclose about Reuse and Industrial Symbiosis. GRI 305 is appropriate for Eco-Design, Renewable Energy, Product as a Service, Industrial Symbiosis and Recycling. Finally, GRI 306 is useful to communicate the CE strategies of Recycling, Reuse, Reverse Logistics, Eco-Design, Industrial Symbiosis, Maintenance/Repair, Refurbishing/Reconditioning/Remanufacturing.

The paper includes implications concerning how to report the implementation of a wide range of CE practices, mainly using GRI 301, 302, 303, 305 and 306. These implications are mainly addressed to SMEs in different economic sectors.

The use of the proposed framework, by improving the transparency and communication of the CE strategies used by companies, may contribute to accelerate the consumer awareness on CE practices fostering the CE transition, especially of SMEs, with a positive effect on society and environment.

This study extends the literature on CE by developing one among the few standardized approaches using the GRI Standards for the disclosure of CE strategies, a topic mainly investigated in the literature with reference to large companies in a few industries. The framework is also useful to explore the implementation of CE strategies across SMEs in different industrial sectors.

To meet energy demand and tackle the challenges posed by global warming, Bagasse-based Cogeneration Power Generation (BCPG) plant in sugar mills have tremendous potential due to large-scale supply of renewable fuel called bagasse. To meet this goal, an integrated framework has been proposed for analyzing performance issues of BCPG.

Intuitionistic Fuzzy Lambda-Tau (IFLT) approach was implemented to compute various reliability parameters. Intuitionistic Fuzzy Failure Mode and Effect Analysis (IF-FMEA) approach has been implemented for studying risk issues results in decrease in plant's availability. Moreover, IF- Technique for Order Performance by Similarity to Ideal Solution (IF-TOPSIS) is implemented to verify accuracy of IF-FMEA approach.

For membership and non-membership functions, availability decreases to 0.0006% and 0.0020% respectively for spread ±15% to ±30%, and further decreases to 0.0127% and 0.0221% for spread ±30% to ±45%. Under risk assessment failure causes namely Storage tank (ST3), Valve (VL6), Transfer pump (TF8), Deaerator tank (DT11), High pressure heater and economiser (HP15), Boiler drum and super heater (BS22), Forced draft and Secondary air fan (FS25), Air preheater (AH29) and Furnace (FR31) with Intuitionistic Fuzzy Hybrid Weighted Euclidean Distance (IFHWED) based output scores – 0.8988, 0.9752, 0.9400, 0.8988, 0.9267, 1.1131, 1.0039, 0.8185, 1.0604 were identified as the most critical failure causes.

Reliability and risk analysis results derived from IFLT and IF-FMEA approaches respectively, to address the performance issues of BCPG is based on the quantitative and qualitative data collected from the industrial experts and maintenance log book. Moreover, to take care of hesitation in expert's knowledge, IF theory-based concept is incorporated so as to achieve more accuracy in analysis results. Reliability and risk analysis results together will be helpful in analyzing the performance characteristics and diagnosis of critical failure causes, which will minimize frequent failure in BCPG.

The framework will help plant managers to frame optimal maintenance policy in order to enhance the operational aspects of the considered unit. Moreover, the accurate and early detection of failure causes will also help managers to take prudent decision for smooth operation of plant.

The results obtained ensure continuous operation of plant by utilizing the bagasse as fuel in boiler and also mitigate the wastages of fuel. If this bagasse (green fuel) is not properly utilized, there remains a dependency on coal-based power plants to meet the power demand. The results obtained are useful for decreasing dependency on coal, and promoting bagasse as the green, and alternative fuel, the emission by burning of these fuels are not harmful for environment and thereby contribute in preventing the environment from harmful effect of GHGs gases.

IFLT approach has been implemented to develop reliability modeling equations of the BCPG unit, and furthermore to compute various reliability parameters for both membership and non-membership function. The ranking results of IF-FMEA are compared to IF-TOPSIS approach. Sensitivity analysis is done to check stability of proposed framework.