duration-prediction
Duration Prediction
Business Case
Problem Statement
Project duration estimation challenges:
- Subjective expert estimates
- Lack of historical benchmarking
- Inaccurate early-stage predictions
- Difficulty comparing similar projects
Solution
Machine learning-based duration prediction using k-Nearest Neighbors and regression models trained on historical project data.
Technical Implementation
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
More from datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
cad-to-data
Convert CAD/BIM files to structured data. Extract element data from Revit, IFC, DWG, DGN files.
154dwg-to-excel
Convert AutoCAD DWG files (1983-2026) to Excel databases using DwgExporter CLI. Extract layers, blocks, attributes, and geometry data without Autodesk licenses.
125drawing-analyzer
Analyze construction drawings to extract dimensions, annotations, symbols, and metadata. Support quantity takeoff and design review automation.
85cost-estimation-resource
Calculate construction costs using resource-based method. Estimate project costs from work items, physical resource norms, and current prices.
63pandas-construction-analysis
Comprehensive Pandas toolkit for construction data analysis. Filter, group, aggregate BIM elements, calculate quantities, merge datasets, and generate reports from structured construction data.
45ifc-data-extraction
Extract structured data from IFC (Industry Foundation Classes) files using IfcOpenShell. Parse BIM models, extract quantities, properties, spatial relationships, and export to various formats.
42