طراحي مدل پيش‌بيني و ارزيابي ظرفيت نوآوري شركت‌هاي دانش‌بنيان با رويكرد استنتاج فازي عصبي- تطبيقي(ANFIS)

Designing a Model for Predicting and Evaluating the Innovation Capacity of Knowledge-based Companies with a Neural-Adaptive Fuzzy Inference System (ANFIS).

ارزيابي ظرفيت نوآوري شركت‌هاي دانش بنيان و پيش‌بيني ميزان ظرفيت نوآوري آن‌ها براي اين شركت‌ها بسيار حائز اهميت است و تصميم در خصوص انتقال يا بسط فناوري شركت تابع ميزان ظرفيت نوآوري است. هدف اصلي اين تحقيق، طراحي مدل ارزيابي ظرفيت نوآوري شركت‌هاي دانش بنيان با رويكرد استنتاج فازي عصبي- تطبيقي است. سيستم استنتاج فازي عصبي - تطبيقي ([1]ANFIS) روش مناسبي براي حل مسائل غيرخطي است. ANFIS تركيبي از روش استنتاج فازي و شبكه عصبي است كه از توانايي هر دو بهره مي‌برد. جامعه تحقيق و نمونه آماري جهت تدوين، اجرا و تست مدل، تمامي شركت‌هاي دانش بنيان پارك فناوري پرديس است كه درنهايت تعداد 180 مورد ارزيابي، انجام‌شده توسط ارزياب‌هاي متخصص جمع‌آوري و مبناي محاسبات مدل قرار گرفت. براي ارزيابي عملكرد مدل، از پارامترهاي مجذور ميانگين مربعات خطا (RMSE)، درصد خطاي نسبي (ε)، ميانگين خطاي مطلق (MAE) و ضريب تبيين (R2) محاسبه گرديد كه به ترتيب مقادير 0136/0، 3/1 درصد، 048/0 و 998/0 به دست آمد كه نشانگر دقت و قابليت اعتماد در پيش‌بيني خروجي مدل است. اين پژوهش از نظر هدف، كاربردي و با توجه به روش گردآوري داده‌ها از نوع توصيفي- پيمايشي است. خروجي اين پژوهش، ﻳﻚ ﺳﻴﺴﺘﻢ اﺳﺘﻨﺘﺎج ﻓﺎزي- عصبي ﻫﻮﺷﻤﻨﺪ (ANFIS) اﺳت

Abstract Assessing the innovation capacity of knowledge-based companies and predicting their innovation capacity is very important for these companies, and the decision to transfer or expand the company's technology depends on the level of innovation capacity. The main purpose of this study is to design a model for assessing the innovation capacity of knowledge-based companies with a neural-adaptive fuzzy inference approach. Nervous-adaptive fuzzy inference system (ANFIS) is a good way to solve nonlinear problems. ANFIS is a combination of fuzzy inference and neural network that utilizes both. The research and statistical sample population for compiling, implementing and testing the model is all the knowledge-based companies of Pardis Technology Park, and finally 180 items were evaluated, collected by expert evaluators and based on model calculations. To evaluate the performance of the model, the parameters of the average error square (RMSE), relative error percentage (e), absolute error average (MAE) and coefficient of explanation (R2) were calculated, which are 0.0136, 1.3%, and 0.048, respectively. an‎d 0.998 was obtained. which indicates the accuracy and reliability of the model output prediction. This research is descriptive-survey in terms of purpose, application, and data collection method. The output of this study is "ANFIS". Introduction: Assessing the innovation capacity of companies is a complex and elusive concept that is difficult to determine. Measuring the capacity for innovation requires quantitative and qualitative considerations. In both cases, the companies are both. an‎d ‌.. Innovative. Therefore, knowledge-based companies that are leading the new economy in the world need to recognize their innovation capacities and be aware of the level of innovation capacity and formulate specific strategies to reach the desired level.