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• IMSL&trade；C 數值程序庫 (CNL) 提供進階的數學與統計程序庫功能，讓程序設計師能夠在利用今日主流的程序語言C/C++開發應用程序時直接嵌入。這些支援 thread safe 的程序皆是依據知名的 IMSL Fortran 程序庫的算法開發而成。
• The IMSL Numerical Libraries have been the cornerstone of high-performance and desktop computing applications in science, technical and business environments for well over three decades. These embeddable mathematical and statistical algorithms are used in a broad range of applications -- including programs that help airplanes fly, predict the weather, enable innovative study of the human genome, predict stock market behavior and provide risk management and portfolio optimization. The algorithms embody the combination of High Performance Computing and High Productivity Computing.Significant benefits can be realized with the product’s ability to accelerate development time, reduce coding hassle, improve quality, and reduce development costs.
• Embeddable Mathematical and Statistical Functionality
• The IMSL Libraries are a comprehensive set of mathematical and statistical functions that programmers can embed into their software applications. The libraries save development time by providing pre-written mathematical and statistical algorithms that can be embedded into C, C# for .NET, Java™ and Fortranapplications, enhancing return on investment and programmer productivity. The IMSL Libraries can also be used from Python using PyIMSL Studio or the PyIMSL wrappers. Beyond choice of programming language, the IMSL Libraries are supported across a wide range of hardware and operating system environments including Windows, Linux, Apple and many UNIX platforms.
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• The IMSL Libraries and support services emphasize user productivity and cost-effectiveness providing asignificant return on investment by saving up to 95% of the time and cost of developing numerical algorithms.
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• Functional areas included in the IMSL Numerical Libraries:
• Mathematics Statistics
• Matrix Operations
• Linear Algebra
• Eigensystems
• Interpolation & Approximation
• Numerical Quadrature
• Differential Equations
• Nonlinear Equations
• Optimization
• Special Functions
• Finance & Bond Calculations
• Genetic Algorithm
• Basic Statistics
• Time Series & Forecasting
• Nonparametric Tests
• Correlation & Covariance
• Data Mining
• Regression
• Analysis of Variance
• Transforms
• Goodness of Fit
• Distribution Functions
• Random Number Generation
• Neural Networks
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• Benefits of Embedding the IMSL® Libraries in Your Analytic Applications
• Accelerate Development
• Analytical building blocks eliminating the need to write code from scratch
• Numerical algorithms are developed, tested, documented, and ready to go
• Save up to 95% of the time required to research and develop algorithms
• Consistent commercial quality interfaces improve developer productivity
• Develop Better Software Applications
• You don't have to worry about coding and testing the numerical algorithms
• Free up your developers' bandwidth for critical application-specific feature development
• Develop Flexible Software Applications
• The IMSL Libraries are written in the standard languages of C, C#, Java, and Fortran
• Embed numerical analysis algorithms seamlessly into existing solutions
• Applications built in C++, Python or any .NET language can easily reference the IMSL Libraries
• Improve Quality and Reduce Uncertainty
• The IMSL Libraries simplify your projects
• A simpler project means a more predictable development and QA schedule
• All IMSL algorithms are fully tested and qualified against proven testing criteria
• QA efforts can focus on core application testing, not algorithm testing
• The IMSL Libraries are fully documented and supported
• Reduce Costs
• The IMSL Libraries save up to 95% of algorithm development costs
• The IMSL Libraries eliminate many hidden costs associated with algorithm development and support:
• Background research
• Debugging and QA
• Porting to your specific environment
• Documentation
• Maintenance
• Scaling for larger deployments
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• IMSL® Library Return on Investment (ROI)
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• Numerical Analysis Algorithm Development: More costly than you may think
• Direct Time and Cost to Develop In-House
• To just research and develop one numerical analysis algorithm, it could take an effort of about 8 weeks.
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• Indirect Time and Cost to Develop In-House
• In addition to direct costs for development, there are additional hidden costs associated with building your own routines, including:
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• Maintenance
• Porting
• Testing and Quality Assurance
• Documentation
• Indirect development efforts could require approximately 16 weeks of work.
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• This represents a total of 24 weeks to develop, test, port, and document one numerical analysis algorithm. Compare this to no more than five days to call, embed, and test an IMSL algorithm.
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• This comparison represents over 95% savings in time and cost!
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• Consider the opportunity costs as your top developers spend their time reinventing the wheel instead of using their domain knowledge to further develop your core application.
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• Finally, who will provide support as developers move on?
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• 應用領域
• 金融服務服務業中的投資組合優化方法
• 保險產業中之風險管理
• 存貨管理與需求預測
• 高效能計算之仿真與模式建構
• 醫學與生物科技系統研發與建構
• ISV 獨立軟件開發商開發應用軟件中內嵌數學計算引擎
• 其它領域
• IMSL C 數值程序庫 6.0 提供更多函數，諸如世界級的線性規劃函數 (Linear Programming) 、類神經網絡預測與許多微分方程函數。除了這些新增功能之外，IMSL C 數值程序庫在目前廣泛被使用的平臺上皆經過完整調校驗證過兼容性、數值正確性與效能。
• 藉由功能強大的 IMSL C# 數值程序庫打造功能完整的商業分析工具
• 今日的商業決策所需要的就是快速反應，以及基礎于穩健可靠的商業分析工具之上，而為達成一個有效且正確的決策，所需的是龐大、豐富與有價值的歷史資料分析。通過全新功能設計的 IMSL C# 數學、統計程序庫之使用，可創造出專屬于您所屬企業的決策支援工具，幫助您發現、了解以及洞悉并進而能夠掌握影響企業內部的種種變因。
• 運用 IMSL C# 數值程序庫，您的應用程序可輕易于 Microsoft .NET 的結構中，開發屬于您企業中前所未有的強大分析工具， IMSL C# 程序庫強大功能的來源在于，其核心基礎中包含了許多常用且有效的分析演算法，例如：求取利潤的極大化（profit maximization）、產品設計優化（product design optimization）、供應鏈效能的優化演算（supply chain efficiency optimization）以及需求預測（demand forecasting）等。
• 常見處理器架構支持：包含 x86-32 bit, x86-64 bit (Xeon-64, Opteron, EM64T), Itanium2, Sun UltraSPARC, IBM Power 等等
• 廣泛的操作系統支持：包含 Linux, Unix, Windows
• 廣泛的編譯器支持：包含 gcc, Intel, Microsoft, Sun, IBM
• 商界的數值分析及數據視覺應用
• JMSL 程序庫完整的收集了數學、統計、財務、數據探勘(data mining)，以及繪圖的類別 (Classes)，它是由 100% Pure Java 撰寫。JMSL 是目前市面上唯一一套結合數學、統計以及繪圖的 Java 程序集。
• 身為現今企業的決策者，必須在壓力下做出既快速且具前瞻性的決策。也因此，他們需要一套比過去更強大更具時效性的企業分析工具，能夠提供他們可信任的運算輸出結果，幫助他們做出自信的決策。
• 擁有類神經網絡(Neural Network)技術的進階預測功能
• JMSL 程序庫包含了類神經網絡的技術，在現行的數據探勘、預測技術中增加了一個選擇。這些類神經網絡的預測類別，提供業界在使用歷史數據建構預測模塊以及對模塊作優化時極大的功能。
• 類神經網絡預測類別最大的特征在于可以仿真人類解決問題的過程，把從歷史數據中獲得的知識應用到新的問題中，并且調整預測的正確性。透過這個功能，企業可以從歷史資料中，例如將過去的成本數據應用到類神經網絡中來預測未來的成本。
• 類神經網絡的訓練應用整合了數據探勘的四個步驟：數據前處理(data preprocessing)、網絡訓練(network training)、網絡預測(network forecasting)以及數據后處理(data post processing)。
• 應用強大的統計功能在先進的應用技術中
• JMSL數值程序庫包含了新的統計算法，協助統計學家以及分析人員來分析非常大量且復雜的數據，例如在生物科技以及生命科學中的應用。
• 其它 JMSL 程序庫中加入的重要部份包含了 heat map 圖形，用在一些包含生命科學的應用，利用顏色來呈現二維的數組。Heat map 圖形加上原來 JMSL 強大廣泛的圖形類別，幫助分析人員利用 Java 來開發進階的數值分析應用。