Multi-target Genetic Programming for Nutrient Assessment in Fish

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Title

Multi-target Genetic Programming for Nutrient Assessment in Fish

Content partner

Victoria University of Wellington

Collection

Open Access Victoria University of Wellington

Description

<strong>The Cyber-Marine project aims to maximise the utility of commercial fish by using Artificial Intelligence (AI) supported tools and non-invasive chemical methods to assess their nutrient content. Vibrational Spectroscopy has proven to be a reliable method to determine molecular characteristics of a product. Particularly, it has gained prominence in evaluating the nutrient level of produce through statistical modelling techniques, such as Partial Least Squared regression (PLSR). This th...

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Format

Research paper

Research format

Scholarly text / Thesis

Thesis level

Masters

Date created

2024

Creator

Amer Hussain

URL

https://figshare.com/articles/thesis/Multi-target_Genetic_Programming_for_Nutrient_Assessment_in_...

Related subjects

Post-harvest fisheries technologies (incl. transportation) / Evolutionary computation / Modelling and simulation / Machine learning not elsewhere classified / Artificial Intelligence / Genetic Programming / Regression / Nutrient Assessment / Multi-target regression / Spectroscopy / Machine Learning / Symbolic Regression / School: School of Engineering and Computer Science / Fish product traceability and quality assurance / Processed non-food agricultural products (excl. wood, paper and fibre) not elsewhere classified / Degree Discipline: Artificial Intelligence / Degree Name: Master of Science / Degree Level: Masters

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