Mapping a Conceptual Model of Colour Forecasting: A Review of Machine Learning Algorithms for Enhanced Prediction Accuracy and Efficiency

Colour forecasting can be defined as the process of predicting future colour acceptances and developing colour stories and palettes that reflect the needs of the consumers. The colour forecasting industry has rapidly evolved by combining data sciences with the intuitive process of colour forecasting, resulting in increased accuracy and efficiency. This review paper studies the various experiments conducted to achieve colour forecasting results by integrating artificial intelligence to analyse big data. The study gives an insight into machine learning applications and other AI models that have provided results in the field opening up future scope for research in image recognition, colour identification, trend analysis and eventual prediction. The paper also discusses the various colour spaces and systems that assist in quantifying and classifying colour data. AI plays a crucial role in colour trend forecasting by analysing large amounts of qualitative and quantitative data. It aids in image recognition, segmentation, and attribute analysis, leading to accurate trend generation. Hybrid AI models show promise in achieving the highest prediction accuracy.