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This study introduces new decision-making tools using bipolar complex fuzzy sets and Aczel-Alsina operations for complex problems. It prioritizes factors for integrating image processing and big data analytics in software development.

Keywords:
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Area of Science:

  • Decision Sciences
  • Fuzzy Logic Systems
  • Computational Intelligence

Background:

  • Real-world decision-making (DM) often involves ambiguous, uncertain, and dual-valued information.
  • Bipolar complex fuzzy set (BCFS) theory integrates bipolar fuzzy sets (BFS) and complex fuzzy sets (CFS) for handling such data.
  • BCFS associates positive membership degree (PMD) and negative membership degrees (Ne-MD) within the complex plane's unit square.

Purpose of the Study:

  • To introduce novel aggregation operators (AOs) within the BCFS framework using Aczel-Alsina (AA) operational laws.
  • To analytically investigate the properties of the proposed BCFCIAAA and BCFCIAAOA operators.
  • To develop and apply a hybrid decision-making model for prioritizing critical factors in image processing and big data analytics integration.

Main Methods:

  • Development of bipolar complex fuzzy Choquet integral Aczel-Alsina averaging (BCFCIAAA) and order averaging (BCFCIAAOA) operators.
  • Analytical study of operator properties including idempotency, monotonicity, and boundedness.
  • Hybrid decision-making model combining DEMATEL and Choquet Integral within the BCFS framework.

Main Results:

  • The study introduces and validates two new aggregation operators for bipolar complex fuzzy sets.
  • A hybrid DEMATEL-CI-BCFS model is developed and applied to a real-world case study.
  • Critical causal factors for IP-BDA integration in software development were identified, including feature extraction, automation, efficiency, and object detection.

Conclusions:

  • The proposed operators and hybrid model offer a robust framework for complex decision-making problems.
  • Findings highlight the significance of feature extraction, automation, and object detection in IP-BDA integration.
  • Actionable insights are provided for decision-makers to enhance software systems through intelligent feature handling and scalable analytics.