Clustering of Faculty by Evaluating their Appraisal Performance by using Feed Forward Neural Network Approach

Bhanuprakash, C.; Nijagunarya, Y. S.; Jayaram, M. A.

doi:10.5815/ijisa.2017.03.05

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…Intelligent network teaching adds intelligent elements to the teaching system through intelligent network and communication technology, making the entire teaching process more intelligent, and the teaching content presented is more diverse, intuitive, and visualized. And it can better meet the different requirements of learners to achieve personalized teaching, which greatly improves the teaching efficiency [ 11 , 12 ]. The intelligent network teaching technology architecture is shown in Figure 2 .The whole architecture diagram includes four parts: communication technology, intelligent network technology, multimedia technology, and students and teachers.…”

Section: Intelligent Teaching Methods For Product Design Majorsmentioning

confidence: 99%

Intelligent Network Teaching of Product Design Specialty Based on Video Image Processing

Gao

Lee

2022

Applied Bionics and Biomechanics

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The product design major was formally established in 2011 and has been an important part of Chinese art education since then. At the same time, it has laid a solid foundation for the development of China’s higher education. Therefore, the product design major occupies an important position in China’s higher education and plays an irreplaceable role in cultivating industrial design talents for the country. With the continuous development and progress of national education, the teaching of product design is also constantly innovating, in order to better improve the teaching effect of product design and cultivate more product design professionals for the country. The purpose of this paper is to study the teaching of product design major based on intelligent network teaching, establish an intelligent network teaching system, and carry out intelligent network teaching experiment of product design major based on this system. The experiment concluded that the overall satisfaction of the students majoring in product design on the intelligent network teaching reached 82%, and the intelligent network teaching mode also increased the outstanding performance rate of the students majoring in product design by 30%.

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Section: Intelligent Teaching Methods For Product Design Majorsmentioning

confidence: 99%

Intelligent Network Teaching of Product Design Specialty Based on Video Image Processing

Gao

Lee

2022

Applied Bionics and Biomechanics

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“…Contemporary methods in evaluation are artificial intelligence techniques that are fuzzy sets and neural networks to minimize the subjective judgement in decision making between an appropriate and inappropriate employee [2]. This approach is to cluster a group of employees in an organization where it considers the membership accuracy with a range of certain values [8]. These techniques are also mostly popular in decision-based structures in proposed systems in engineering communications [9] and in face detection [10].…”

Section: Introductionmentioning

confidence: 99%

A Neural-Fuzzy Network Approach to Employee Performance Evaluation

Escolar-Jimenez¹,

Matsuzaki²,

Gustilo³

2019

IJATCSE

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This neuro -fuzzy system enables the algorithm to identify performing and non-performing employees as organizations currently use several traditional employee evaluation performance methods that utilizes different approaches that are inaccurate and subjective by nature and usually deficient in approximating the accurate capability and nature of employee performance. Results revealed that this artificial intelligence technique utilizing the neuro-fuzzy profiling system, optimizes the objective function in the employee quality evaluation and determines the most distinctive employees deserving career advancement or those who further need appropriate training and development in the achievement, leadership and behavior categories. Since the coefficients of Neural Network can be tuned to the manager's evaluation results, the logic of the overall judgment can be adjusted to the characteristics of the department. The evaluation of this system is also performed with the same evaluation logic of the objective input values thus, the objectivity and transparency of the evaluation are extremely high. This enables HR and decision makers in the organization to truly understand employee strengths and weaknesses that is also an essential part in promoting a positive company culture unlike the traditional employee performance evaluation methods still being adopted by many organizations at present that is impaired with unreliability and rating errors.

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“…These parameters can be derived with the help of a confusion matrix. Table 2 presents a confusion matrix [28] for a binary class that indicates correct and incorrect classifications. Previous studies [29,30] show that accuracy is not an appropriate measure to evaluate the performance of classifying imbalanced dataset.…”

Section: Evaluation Parametersmentioning

confidence: 99%

A Hybrid Approach for Class Imbalance Problem in Customer Churn Prediction: A Novel Extension to Under-sampling

Salunkhe¹,

Mali²

2018

IJISA

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Abstract-Customer retention is becoming a key success factor for many business applications due to increasing market competition. Especially telecom companies are facing this challenge with a rapidly increasing number of service providers. Hence there is need to focus on customer churn prediction in order to detect the customers that are likely to churn i.e. switch from one service provider to another. Several data mining techniques are applied for classifying customers into the churn and non-churn category. But churn prediction applications comprise an imbalanced distribution of the dataset.One of the commonly used techniques to handle imbalanced data is re-sampling of data as it is independent of the classifier being used. In this paper, we develop a hybrid re-sampling approach named SOS-BUS by combining well known oversampling technique SMOTE with our novel under-sampling technique. Our methodology aims to focus on the necessary data of majority class and avoid their removal in order to overcome the limitation of random under-sampling. Experimental results show that the proposed approach outperforms the other reference techniques in terms of Area under ROC Curve (AUC).

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Clustering of Faculty by Evaluating their Appraisal Performance by using Feed Forward Neural Network Approach

Cited by 7 publications

References 4 publications

Intelligent Network Teaching of Product Design Specialty Based on Video Image Processing

Intelligent Network Teaching of Product Design Specialty Based on Video Image Processing

A Neural-Fuzzy Network Approach to Employee Performance Evaluation

A Hybrid Approach for Class Imbalance Problem in Customer Churn Prediction: A Novel Extension to Under-sampling

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