Chen Jing
Community@spiral-edwin · No. 866, yuhangtang Road, Xihu District, Hangzhou, Zhejiang Province
I'm a student in Zhejiang University. Eager to learn on Github and contribute my part to this community.
Agent Skills by Chen Jing
Showing 42 vetted skills indexed across 2 GitHub repositories.
modular-modeler
Build modular system models by composing Environment, Agent, Policy, Simulator components in Python.
lstm-forecaster
Forecast time series values using LSTM/GRU networks in TensorFlow/Keras.
robustness-check
Analyze model robustness via parameter perturbation sensitivity and equilibrium stability.
visual-engineer
Generate publication-quality scientific figures with Matplotlib and Seaborn.
genetic-algorithm
Solve discrete and combinatorial optimization problems using a genetic algorithm in Python.
fuzzy-evaluation
Convert linguistic judgments into fuzzy memberships and aggregate weighted factors for decision-making.
integer-programming
Solve integer programming problems with binary and integer variables using SciPy milp and MATLAB intlinprog.
reaction-diffusion
Simulate reaction-diffusion PDEs on 1D/2D domains with configurable coefficients.
grey-forecaster
Forecast short-term time series with GM(1,1) using 4-10 data points.
multi-objective-optimization
Generate Pareto-frontier solutions using NSGA-II, MOEA/D, and weighted-sum methods.
ml-regressor
Train Random Forest and XGBoost regression models on tabular data.
grey-relation
Rank factor influence using Grey Relational Analysis with Python and MATLAB templates.
sensitivity-master
Perform Morris and Sobol sensitivity analyses on nonlinear multi-parameter models with SALib.
automated-sweep
Automate parameter sweeps and optimization for mathematical models.
minimax-programming
Transform minimax and max-min objectives into standard constrained programs.
xlsx
Clean, normalize, and analyze Excel and CSV data for mathematical modeling workflows.
Extract text and tables from PDFs and merge validated MCM/ICM submission documents.
shortest-path
Compute shortest paths in weighted graphs using Dijkstra, Bellman-Ford, Floyd-Warshall, and A*.
nonlinear-programming
Solve nonlinear optimization problems with SciPy solvers like SLSQP.
latex-transformer
Convert Markdown drafts into LaTeX-formatted content for MCM/ICM papers.
minimum-spanning-tree
Find a minimum-weight spanning tree using Prim's and Kruskal's algorithms.
topsis-scorer
Compute TOPSIS scores and rank alternatives from a decision matrix.
network-centrality
Compute degree, betweenness, closeness, eigenvector centrality, and PageRank for network nodes.
dynamic-programming
Solve multi-stage optimization problems with memoization and recurrence relations.
Frequently Asked Questions About Chen Jing
FAQPage SchemaWhat tasks can I accomplish with SPIRAL-EDWIN's skills?▼
You can build and solve mathematical models for MCM/ICM competitions: linear, nonlinear, integer, and dynamic programming; LSTM/ARIMA/grey forecasting; Monte Carlo and reaction-diffusion simulation; graph algorithms like Dijkstra and PageRank; plus TOPSIS, AHP, and fuzzy decision evaluation.
Who are these skills designed for?▼
They target mathematical modeling competitors, particularly MCM/ICM teams, and students or researchers needing optimization, forecasting, sensitivity analysis, and decision-scoring capabilities. The author is a Zhejiang University student, and templates are optimized for time-sensitive competition data preparation and paper writing.
What runtimes and libraries do these skills require?▼
Skills rely on Python scientific libraries including SciPy, NumPy, pandas, scikit-learn, TensorFlow/Keras, statsmodels, pmdarima, SALib, NetworkX, Matplotlib, and Seaborn. Some templates also support MATLAB functions such as intlinprog for integer programming tasks.
Are SPIRAL-EDWIN's skills open source?▼
The skills are published publicly on GitHub under the SPIRAL-EDWIN account. The skill-creator skill references complete license terms in its LICENSE.txt file; other skills carry no explicit license, so users should review the repository before redistribution or commercial use.
How do the skills support MCM/ICM paper submission?▼
Dedicated skills extract text, equations, and tables from academic PDFs, merge final submission PDFs with code appendices, validate page-limit compliance, convert Markdown drafts to LaTeX, generate AI-usage appendix documentation, and produce screenshot-ready HTML/CSS/SVG/React visualizations for manuscript inclusion.