CITATION.cff

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "Self-Play Energy Forecasting & Anomaly Detection"
abstract: "A machine learning system that adapts the propose→solve→verify self-play approach to time series forecasting and anomaly detection in energy consumption data. Features household-level prediction with distribution network validation using UK-DALE, London Smart Meters, and SSEN LV feeder data."
authors:
  - family-names: "Your Last Name"
    given-names: "Your First Name"
    orcid: "https://orcid.org/0000-0000-0000-0000"
    email: "your.email@example.com"
    affiliation: "Your University"
repository-code: "https://github.com/USERNAME/FYP-Predictive_Anomaly_Detection"
url: "https://github.com/USERNAME/FYP-Predictive_Anomaly_Detection"
license: MIT
keywords:
  - "energy forecasting"
  - "anomaly detection"
  - "time series"
  - "self-play learning"
  - "machine learning"
  - "smart grids"
  - "distribution networks"
  - "household energy"
  - "neural networks"
  - "reinforcement learning"
version: "0.1.0"
date-released: "2025-09-23"
preferred-citation:
  type: thesis
  title: "Self-Play Energy Forecasting & Anomaly Detection: A Self-Play Approach to Household Consumption Prediction with Distribution Network Validation"
  authors:
    - family-names: "Your Last Name"
      given-names: "Your First Name"
      orcid: "https://orcid.org/0000-0000-0000-0000"
  institution:
    name: "Your University"
  department: "Department of Computer Science"
  thesis-type: "Final Year Project"
  year: 2025
  url: "https://github.com/USERNAME/FYP-Predictive_Anomaly_Detection"