پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 163 |
| تعداد شماره‌ها | 6,767 |
| تعداد مقالات | 72,886 |
| تعداد مشاهده مقاله | 132,094,355 |
| تعداد دریافت فایل اصل مقاله | 103,637,638 |
Modeling job performance using Optimized Adaptive Neuro-Fuzzy Inference System | ||
| Industrial Management Journal | ||
| مقاله 7، دوره 6، شماره 1، تیر 2014، صفحه 111-136 اصل مقاله (1.3 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2014.52238 | ||
| نویسندگان | ||
| Mahmoud Moradi* ؛ Behnaz Zanjani؛ Ali Jamali | ||
| چکیده | ||
| Using current employee performance data to predict the future behavior of the applicants is an interesting area which can broaden new horizons of knowledge lay in the organization. Because of inherent ambiguity and uncertainty, cognitive limitations of the human mind make unknown behaviors of very complex systems difficult to predict. As a consequence, it is necessary to model the imprecise modes of reasoning to make rational decisions in an environment of uncertainty and imprecision. In this paper, artificial intelligence and advanced algorithms is introduced as an Adaptive Neuro-Fuzzy Inference Optimized System in order to model the job performance. The correlation coefficient is 0.9956 which indicates high accuracy of extracted model, minimum error and maximum adaptability to predict job performance with actual performance. This approach provides an effective tool for managers in order to avoid subjective judgment errors inherent in human decision making. | ||
| کلیدواژه‌ها | ||
| Job performance؛ Predicting؛ modeling؛ Optimizing؛ Adaptive Neuro-Fuzzy Inference Optimized System | ||
|
آمار تعداد مشاهده مقاله: 2,679 تعداد دریافت فایل اصل مقاله: 1,649 |
||
سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب