Search alternatives:
policy implementation » practical implementation (Expand Search)
model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
policy implementation » practical implementation (Expand Search)
model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
-
181
Marketing Campaign Analysis.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
-
182
Visitor Segmentation Validation Accuracy.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
-
183
Integration of VAE and RNN Architecture.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
-
184
-
185
-
186
Table 1_Analysis of distribution equilibrium and influencing factors for older adult meal service facilities in mainland China.xlsx
Published 2025“…A multiple linear regression model was applied to explore the relationships between older adult meal services and factors such as population, economy, infrastructure, geography, and policies.…”
-
187
Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"
Published 2024“…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…”
-
188
<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b>
Published 2025“…</p><p dir="ltr">Models: R code to explore different models for implementation via Python in ArcGIS</p><p dir="ltr">!…”
-
189
Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection
Published 2025“…<p dir="ltr">Python image preprocessing and model implementation for research of "Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection".…”
-
190
<b>Data Availability</b>
Published 2025“…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…”
-
191
<b>Data Availability</b>
Published 2025“…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…”
-
192
<b>Algorithm Pseudocode</b>
Published 2025“…The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …”
-
193
Reproducible Code and Data for figures
Published 2025“…<br>✅ <b>Generated Figures</b> – High-resolution images illustrating model outputs and analytical results.<br>✅ <b>Machine Learning Models</b> – Implementation of <b>K-Nearest Neighbors (KNN) regression</b> with different distance metrics (<b>Mahalanobis, Fuzzy Mahalanobis, Euclidean</b>).…”
-
194
Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space
Published 2025“…/CAH-GKGE/model/supplementary instruction.md </p>…”
-
195
Supplementary Material
Published 2025“…The supplementary material includes the full Python-based implementation of the AI-driven optimization framework described in the manuscript. …”
-
196
A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification
Published 2025“…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…”
-
197
NanoDB: Research Activity Data Management System
Published 2024“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”
-
198
Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series
Published 2025“…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…”
-
199
A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture
Published 2025“…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …”
-
200
Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas
Published 2025“…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…”