طراحی مدل سیستم استنتاج فازی عصبی - تطبیقی ( ANFIS) برای ارزیابی و پیش‌بینی سطح مدیریت دانش سازمان با محوریت نوآوری.

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دکترای مدیریت تکنولوژی، دانشگاه آزاد اسلامی، تهران، ایران.

2 استاد گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران.

چکیده

در سال‌های اخیر مدیریت دانش به یک موضوع مهم و حیاتی در تمامی سازمان‌ها تبدیل‌شده است. یکی از عوامل مؤثر در ایجاد و گسترش نوآوری، مدیریت دانش است. با نوآوری، برتری‌های بلندمدت سازمان در عرصه‌های رقابتی حفظ شود. ارزیابی و پیش‌بینی سطح مدیریت دانش برای مدیران بسیار بااهمیت است. در میان روش‌های نوین مدل‌سازی، سیستم‌های فازی از جایگاه ویژه‌ای در زمینه‌های مختلف علوم برخوردارند. این پژوهش از نظر هدف، کاربردی و با توجه به روش گردآوری داده‌ها از نوع پیمایشی است. سیستم استنتاج فازی عصبی - تطبیقی (ANFIS) روش مناسبی برای حل مسائل غیرخطی است. این روش، ترکیبی از روش استنتاج فازی و شبکه عصبی مصنوعی است که از مزایای هردو روش بهره می‌برد. در این تحقیق تعداد 5 مؤلفه اصلی برای سنجش و پیش‌بینی سطح مدیریت دانش سازمان، به عنوان ورودی سیستم استنتاج فازی انتخاب گردید. برای ارزیابی عملکرد مدل از پارامترهای مجذور میانگین مربعات خطا (RMSE)، درصد خطای نسبی(ε)، میانگین خطای مطلق(MAE) و ضریب تبیین (R2) استفاده‌شده است که به ترتیب مقادیر 12/0 ، 0.0152%، 036/0 و 995/ به‌دست‌آمده است و این نشانگر دقت و قابلیت اعتماد به مدل مذکور است.. خروجی این پژوهش، ﻳﻚ ﺳﻴﺴﺘﻢ اﺳﺘﻨﺘﺎج ﻓﺎزی ﻫﻮﺷﻤﻨﺪ (ANFIS) است.

کلیدواژه‌ها


عنوان مقاله [English]

Designing a Model of Neural-Adaptive Fuzzy Inference System (ANFIS) to Evaluate and Predict Organizational Knowledge Management Level with Innovation Focus.

نویسندگان [English]

  • Amir Hamzeh Alinejad 1
  • Adel Azar 2
1 Department of Industrial Management, Faculty of Management, Central Tehran, Islamic Azad University, Tehran.
2 Professor, Department of Industrial Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
چکیده [English]

In recent years, knowledge management has become a vital issue in all organizations. Knowledge management is one of the effective factors in creating and expanding innovation. With innovation, the long-term advantages of the organization are maintained in the competitive arena. Evaluating and predicting the level of knowledge management for managers is very important. Among the new methods of modeling, fuzzy systems have a special place in different fields of science. The purpose of this research is applied and according to data collection method is survey. The Neural-Adaptive Fuzzy Inference System (ANFIS) is a good method for solving nonlinear problems. This method combines fuzzy inference method and artificial neural network which benefits from both methods. In this study, five main components were selected as inputs for fuzzy inference system to measure and predict the level of knowledge management of the organization. For evaluating the model performance, the parameters of mean square error of error (RMSE), percentage of relative error (ε), mean absolute error (MAE) and coefficient of explanation (R2) were used. Their values are 0.12, 0.0152%, 0.036 and 0.995. This indicates the accuracy and reliability of the model. The output of this study is the neural-adaptive fuzzy inference system (ANFIS).

کلیدواژه‌ها [English]

  • Knowledge Management
  • Innovation
  • Adaptive Neural Fuzzy Inference System (ANFIS)
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