AI Statistical Data Analysis for Mainframe Performance

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Solution Overview

Problem

Current methods for analyzing statistical data in computing environments require human expertise and are time-consuming, prone to errors, and inefficient in automatically detecting computer program performance issues, especially in complex systems like mainframe computers.

Innovation Solution

A software tool that utilizes machine learning models and experience-derived mathematical algorithms to analyze dynamic statistical data, automatically detecting potential performance issues by categorizing and processing data into actionable improvement values, thereby reducing the need for manual analysis and expertise.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If human expertise is used to analyze statistical data, then measurement precision is improved, but loss of time increases and productivity decreases

Engineering Contradiction:

Improveperformance issue detection accuracyVSAvoidanalysis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-service by automatically analyzing statistical data using embedded AI models and mathematical algorithms without requiring human intervention. The analysis process is autonomous, where the system categorizes data, identifies patterns, detects performance issues, and generates recommendations independently, thereby eliminating time loss while maintaining detection accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical human analysis process with an automated computational system. AI models and mathematical algorithms substitute for human expertise in analyzing statistical data, performing pattern recognition, anomaly detection, and performance optimization recommendations automatically, thus reducing time consumption while preserving measurement precision.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual analysis methods are used, then reliability is improved, but productivity decreases

Engineering Contradiction:

Improveanalysis accuracyVSAvoiddata analysis throughput

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system enables continuous automated analysis of statistical data without interruption. The AI models continuously process data streams, constantly detecting performance issues and generating recommendations in real-time, maintaining both high reliability through consistent analytical performance and high productivity through uninterrupted processing.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

Manual analysis is replaced with automated computational algorithms that operate continuously and simultaneously on large datasets. The mathematical models and AI techniques perform complex analytical tasks automatically, achieving both high reliability in detection accuracy and high productivity in analysis throughput.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated analysis tools are used, then productivity is improved, but measurement precision deteriorates

Engineering Contradiction:

Improveanalysis speedVSAvoidperformance issue detection accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system changes the parameters of analysis by transforming statistical data into standardized formats that AI models can process efficiently. Through parameter transformation and normalization, the system maintains measurement precision while enabling high-speed automated analysis. The mathematical algorithms adjust data parameters to optimize both accuracy and processing speed.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent substitutes manual analytical processes with sophisticated computational algorithms that achieve both high productivity and measurement precision. The AI models are designed to maintain detection accuracy while processing data at automated speeds, eliminating the trade-off between speed and precision through advanced computational techniques.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Measurement precision

If complex mathematical algorithms are applied, then measurement precision is improved, but device complexity increases

Engineering Contradiction:

Improvestatistical data analysis accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary layer of standardized data formats and pre-processed statistical representations that simplify the interface between raw data and complex AI analysis algorithms. This intermediary structure allows complex mathematical algorithms to operate on simplified data representations, maintaining measurement precision while reducing the apparent system complexity through abstraction and standardization.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250013666A1Dynamic statistical data analysis

Publication Date: 2025.01.09 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A method, computer program product, and computer system are provided for analyzing statistical data. The statistical data is categorized into a plurality of datasets. A record field of a dataset of the plurality of datasets is selected. An artificial intelligence process is applied to the record field to generate an improvement value. A program corresponding to the record field is processed according to the improvement value.