A Multi-Criteria decision making (MCDM) methodology for high temperature thermochemical storage material selection using graph theory and matrix approach

Hosouli, Sahand; Elvins, Jonathon; Searle, Justin; Boudjabeur, Samir; Bowyer, Jordan; Jewell, Eifion

doi:10.1016/j.matdes.2023.111685

Cited by 16 publications

(6 citation statements)

References 56 publications

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“…Data-driven MCDM models have been utilized in energy systems to optimize energy generation, distribution, and consumption. In a study by Hosouli et al [44], a data-driven MCDM model based on machine learning algorithms was proposed for energy demand forecasting. The model utilized historical energy consumption data, weather data, and socio-economic factors to predict future energy demand at different time horizons.…”

Section: Data-driven Mcdm Modelsmentioning

confidence: 99%

“…Exploring the potential of AI and ML algorithms, such as neural networks, genetic algorithms, and reinforcement learning, in MCDM can lead to more efficient and accurate decision support systems. • Handling big data and real-time decision-making: With the advent of big data technologies, there is a need for MCDM methods that can handle large volumes of data and enable realtime decision-making [44,45]. Developing MCDM approaches that can effectively process and analyze big data streams, incorporate real-time updates, and adapt to dynamic decision environments will be crucial.…”

Section: Future Directions In Mcdm Researchmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Review of Multiple Criteria Decision-Making (MCDM) Methods: Advancements, Applications, and Future Directions

Sahoo¹,

Goswami²

2023

Decis. Mak. Adv.

176

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This research paper presents a comprehensive review of Multiple Criteria Decision-Making (MCDM) methods, encompassing their advancements, applications, and future directions. The study begins with an introduction emphasizing the significance of MCDM in complex decision-making scenarios. Through a systematic literature review, recent developments in MCDM techniques are examined, including multi-objective methods, fuzzy-based approaches, data-driven models, and hybrid methodologies. The strengths and limitations of each method are critically analyzed. Furthermore, the paper investigates the diverse applications of MCDM in domains such as business, engineering, environment, healthcare, and public policy, highlighting the practical implications through real-world case studies. The study then identifies emerging trends and challenges in MCDM research, discussing the integration of MCDM with emerging technologies, enhancing robustness and adaptability, addressing uncertainty, and identifying unexplored domains for potential application. This comprehensive review serves as a valuable resource for decision-makers and researchers, providing insights into the advancements, applications, and future directions of MCDM methods.

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Section: Data-driven Mcdm Modelsmentioning

confidence: 99%

Section: Future Directions In Mcdm Researchmentioning

confidence: 99%

A Comprehensive Review of Multiple Criteria Decision-Making (MCDM) Methods: Advancements, Applications, and Future Directions

Sahoo¹,

Goswami²

2023

Decis. Mak. Adv.

176

View full text Add to dashboard Cite

show abstract

“…In this model, independent spaces, such as rooms, corridors, and staircases, are treated as vertices, while channels that allow for the direct transmission of smoke between two independent spaces are treated as edges. Their unique topological structure allows them to exhibit excellent properties in various algorithmic scenarios, such as dynamic programming, shortest path search in navigation, and data compression [25]. In high-rise buildings, rooms, corridors, and vertical passages where fires may occur are represented as nodes, while the possible propagation directions between nodes are represented as edges.…”

Section: A Prediction Model For Smoke Spread Pathmentioning

confidence: 99%

A Real-Time Pre-Response Experiment System for High-Rise Building Fires Based on the Internet of Things

Zhao

Zhu

2023

Fire

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The primary objective of the current fire protection system in high-rise buildings is to extinguish fires in close proximity to the detectors. However, in the event of rapidly spreading fires, it is more effective to limit the transmission of fire and smoke. This study aims to develop an IoT-based real-time pre-response system for high-rise building fires that is capable of limiting the spread of fire and smoke. The proposed system collects fire data from sensors and transmits them to a cloud computer for real-time analysis. Based on the analysis results, the cloud computer controls the actions of alarm devices, ventilation equipment, and fine water mist nozzles. The system can dynamically adjust the entire system’s behavior in real time by adopting pre-response measures to extinguish fires and limit the spread of fires and smoke. The system was tested on a simulation platform similar to actual high-rise buildings to evaluate its impact on fires and smoke. The results demonstrate the system’s effectiveness in extinguishing fires and suppressing the spread of fires and smoke.

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“…Directed Acyclic Graphs (DAGs) are widely used data structures in computer science due to their unique topological structure, which allows them to exhibit excellent properties in various algorithmic cases, such as dynamic programming, shortest path searches in navigation, and data compression [17]. In the context of high-rise buildings, rooms, corridors, and vertical passages that may contain smoke in the event of a fire are represented as nodes, and the possible propagation directions between nodes are represented as edges.…”

Section: Representing a High-rise Building As A Dag Network Modelmentioning

confidence: 99%

A Prediction Model for Smoke Spread Path in High Rise Building Fires Based on Graph Theory

Zhao

Zhu

2023

Fire

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To satisfy the demand for rapid prediction of smoke transmission paths in high-rise building fires, a graph-based model was developed. The model represents a high-rise building as a Directed Acyclic Graph (DAG) grid model and employs computer simulation to determine the smoke transmission path and generate prediction results. The results were compared with those from similar simulations and were found to be consistent, indicating the feasibility and objective nature of the prediction results. Compared to other methods, this model has a shorter modeling time and can quickly provide prediction results. Furthermore, it can be applied to buildings of any structure, thus serving as a reference for smoke control design in high-rise building fire protection systems, particularly in cases involving complex internal structures.

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A Multi-Criteria decision making (MCDM) methodology for high temperature thermochemical storage material selection using graph theory and matrix approach

Cited by 16 publications

References 56 publications

A Comprehensive Review of Multiple Criteria Decision-Making (MCDM) Methods: Advancements, Applications, and Future Directions

A Comprehensive Review of Multiple Criteria Decision-Making (MCDM) Methods: Advancements, Applications, and Future Directions

A Real-Time Pre-Response Experiment System for High-Rise Building Fires Based on the Internet of Things

A Prediction Model for Smoke Spread Path in High Rise Building Fires Based on Graph Theory

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