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APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY期刊基本信息

  • 簡稱:APPL STOCH MODEL BUS
  • 大類:數學
  • 小類:數學跨學科應用
  • ISSN:1524-1904
  • IF值:1.124
  • 周期:Quarterly
  • 是否SCI:SCIE
  • 是否OA:No
  • 出版地:ENGLAND
  • 年文章數:46
  • 審稿速度:>12周,或約稿
  • 平均錄用比例:容易
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APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY中文簡介

ASMBI -《商業和工業中的應用隨機模型》(前身為《應用隨機模型和數據分析》)于1985年首次出版,發表了關于隨機模型、數據分析及其在商業、金融、保險、管理和生產等方面的應用的論文。2007年ASMBI成為國際商業和工業統計學會的官方期刊()。主要目標是發表論文,包括技術和實踐方面的,提出解決現實問題的新結果,或在這方面有很大潛力。數學的嚴謹性、創新的隨機模型和完善的應用程序是經過非常有選擇性的評審過程后發表論文的關鍵因素。《華爾街日報》是非常開放的新思想,如科學數據和大數據所帶來的問題在工程業務和行業或不確定性量化,以及傳統的,如可靠性、質量控制、實驗設計、管理流程、供應鏈和庫存,保險、計量經濟學、金融建模(提供了論文相關的問題)。該雜志還對研究商業和工業決策對環境、醫療保健和社會生活的影響的論文感興趣。當與可靠的應用程序和創新的模型相結合時,最先進的計算方法也非常受歡迎。

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY英文簡介

ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process.The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.

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