Informatica

Seismic hazard analysis plays a vital role in evaluating the potential earthquake risk in a given region. Northeast India is one of the most seismically active zones due to its tectonic positioning at the collision boundary of the Indian and Eurasian plates. This study aims to implement a comprehensive Seismic Hazard Assessment (SHA) framework using Fuzzy Multi-Criteria Decision Making (MCDM) techniques to improve the accuracy and reliability of Peak Ground Acceleration (PGA) estimates in Northeast India. The methodology integrates Trapezoidal Fuzzy Full Consistency Method (TrF-FUCOM) and Neutrosophic-TOPSIS under Single Valued Neutrosophic Set (SVNS) environment (Neutrosophic-TOPSIS), effectively addressing the limitations of traditional seismic hazard assessment methods, particularly in selecting and weighting Ground Motion Prediction Equations (GMPEs). An extensive earthquake catalogue covering the period from 1762 to 2024 has been analysed, and after declustering, fault zones have been delineated based on earthquake density along active faults. The analysis provides a detailed spatial distribution of Peak Ground Acceleration (PGA) across the region, with the highest PGA value reaching 1.43g using the Deterministic Seismic Hazard Assessment (DSHA) method. The findings of this study offer crucial insights for disaster preparedness, urban planning, and the design of earthquake-resistant infrastructure, helping to mitigate seismic risks and enhance the resilience of communities in Northeast India.

The accelerated progress of aquaponics offers a promising remedy for food production in arid regions, where success heavily hinges on sustaining optimal water quality parameters of aquaponic system. However, managing water parameters in large-scale aquaponic farms, given their complex and interconnected nature, poses significant challenges. Various control approaches have been introduced over the years, but selecting the most suitable one is vital for ensuring stability, efficiency, and high productivity. In this study, a novel fuzzy-based Multiple Criteria Decision Making (MCDM) methodology is proposed, which combines the Intuitionistic Fuzzy Ordinary Priority Approach (OPA-IF) with the Neutrosophic-TOPSIS strategy. This methodology aims to identify the most appropriate control strategy for large-scale aquaponic systems. The OPA-IF analysis reveals that the ‘Capability to Handle MIMO Systems’ is the most critical criterion, leading to the conclusion, through the Neutrosophic-TOPSIS approach, that ‘Model Predictive Control (MPC)’ is the optimal choice for managing large-scale aquaponic systems. Additionally, a comparative analysis using the BWM-Neutrosophic-TOPSIS strategy further supports the findings of the proposed method. The results are further validated through statistical analysis and sensitivity testing, ensuring their robustness and reliability. Overall, this study not only contributes to the scientific understanding of control strategies in aquaponics but also offers practical insights for farmers and aquaponic practitioners. The ultimate goal is to enhance the sustainability and efficiency of aquaponic systems, promoting their adoption and long-term success in sustainable food production.

In this study, Intuitionistic Fuzzy Consistency Method (IF-FUCOM) and Grey Relation Analysis (GRA) were combined to assess the effects of Bacillus subtilis bacteria on concrete properties, as well as to determine the optimal bacteria concentration and curing day. Three different concentrations of bacteria were added to the mortar mixes, like 103, 105, and 107 cells/ml of water. Mortar samples were left to cure for 7 days, 14 days, and 28 days to evaluate compressive strength, water absorption, crack healing. According to the proposed algorithm, 105 bacteria are the optimal concentration, while 28 days is the ideal curing time.