A Systematic Literature Review on Machine Learning Techniques for Predicting Household Water Consumption

The Excel file "A Systematic Literature Review on Machine Learning Techniques for Predicting Household Water Consumption" is structured to document a systematic review process. It contains six sheets, each representing a stage in the literature review. Here's a breakdown of each sheet:

1. Initial Set

Contains the raw collection of research articles from databases like Scopus.

Includes fields like: title, author, journal, year, source, and abstract.

2. Duplicates Removed

Similar to the Initial Set but with duplicate entries removed.

Retains the same structure and content fields.

3. Abstract Screened

Articles that passed the abstract screening stage.

Same format as above, suggesting relevance was judged based on abstract content.

4. Corpus Screened

Articles that passed a deeper screening phase.

Likely assessed on fuller content, with some articles having missing abstracts (None values present).

5. Quality Assessment

Evaluates articles based on 10 quality criteria (e.g., clarity of objectives, use of visuals, replicability).

Scores are numerical (0–1) and include calculated metrics like Quality of the report, Credibility, Rigor, and Relevance.

6. Final Set

The most relevant and high-quality studies selected for the review.

Detailed columns include:

ML Technique (MLT)

MLT Characteristic

Type of Evaluation

Selection Factors

Benefits and Challenges

Type of Publication and DOI