List of Articles Human Resources Productivity

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  1 - Introducing a cost-effective engineering model for increasing productivity indicators
  Mehrdad masoudnejad Morteza Rayati Damavandi Seros Gholampoor Dahaki
  The importance and role of human resources in organizations and enterprises, economic and industrial as the stimulus of the economic cycle of the society is not at all anybody. But today, work-related accidents, as one of the key factors in the loss of efficient human r More

  The importance and role of human resources in organizations and enterprises, economic and industrial as the stimulus of the economic cycle of the society is not at all anybody. But today, work-related accidents, as one of the key factors in the loss of efficient human resources and the loss of capital and time, are a threat to the development and development of any country. These incidents have a huge impact on the productivity of various industry workers and ultimately on the economy of society.In most of the studies, cost estimates have often been used to calculate the costs of safety in the workplace, and usually the cost of any damage or cost of the entire accident is calculated, and despite the importance of reducing productivity from work-related accidents , This important is still ignored. Therefore, in the present study, a multi-criteria decision-making methodology for presenting a cost-effective engineering model based on productivity indicators has been used. The results of this study showed that, according to the criteria, the priority of conducting classes and training courses, creation of safety regulations in administrative and manufacturing departments, investment in medical care, safety equipment and machinery purchase, equipment and technology The newest have the greatest impact on engineering safety costs based on productivity indicators Manuscript profile
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  2 - The Causal Structure Model of Human Resources Productivity, Job Satisfaction, Organizational Citizenship Behavior and Organizational Commitment in Water and Wastewater Industry (Case Study: Alborz Province
  Ali Badizadeh Gholam Reza Rezaifar
  Empowered human resource in any organization is an effective factor for success of organization. Human resource productivity as a key factor is proposed. The Aim of this study is to make causal model for human resource productivity, job satisfaction, organizational citi More

  Empowered human resource in any organization is an effective factor for success of organization. Human resource productivity as a key factor is proposed. The Aim of this study is to make causal model for human resource productivity, job satisfaction, organizational citizenship behavior and organizational commitment. Standard questionnaire as research tool and statistical population of study was official and contract employees of Alborz Province water and Wastewater Company. Partial Least square method is used for modeling. Findings show that there is significant and positive relation between human resource productivity with job satisfaction, organizational citizenship behavior and organizational commitment .Also, there are significant and positive relation between organizational commitment with job satisfaction and organizational citizenship behavior .Finally, there is significant and positive relation between job satisfaction and organizational citizenship behavior. Further research advices have been proposed at the end. Manuscript profile
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  3 - Using different learning algorithms in the stock price prediction by using neural networks
  Reza Kiyani Mavi Kamran Sayadi Nik
  Stock price prediction is a very important financial topic, and is considered a challenging task and worthy of the considerableattention received from both researchers and practitioners. Stock price series have properties of high volatility, complexity,dynamics and turb More

  Stock price prediction is a very important financial topic, and is considered a challenging task and worthy of the considerableattention received from both researchers and practitioners. Stock price series have properties of high volatility, complexity,dynamics and turbulence, thus the implicit relationship between the stock price and predictors is quite dynamic. Hence, it isdifficult to tackle the stock price prediction problems effectively by using only single soft computing technique.In this research, in the first step, the possibility of predicting stock price of National Iranian Copper Industries Company wasstudied. Then, for predicting of stock price after one day neural ¬network of MLP by learning algorithm of Levenberg-Marquardt were used. Then optimize structure of neural network was trained with the standard BP algorithm, the learningrate is 3/0 has the best performance. And for this learning rate, sensitive of standard BP algorithm was calculated to minimizelocal. At the end, standard BP algorithm with momentum is used. The results showed that predicting by standards BPalgorithm with momentum is better than the standard BP algorithm. Manuscript profile
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  4 - Using different learning algorithms in the stock price prediction by using neural networks
  Ahmad Esa Khani Akbar Hassan pour Sima Naghde froshha
  Stock price prediction is a very important financial topic, and is considered a challenging task and worthy of the considerableattention received from both researchers and practitioners. Stock price series have properties of high volatility, complexity,dynamics and turb More

  Stock price prediction is a very important financial topic, and is considered a challenging task and worthy of the considerableattention received from both researchers and practitioners. Stock price series have properties of high volatility, complexity,dynamics and turbulence, thus the implicit relationship between the stock price and predictors is quite dynamic. Hence, it isdifficult to tackle the stock price prediction problems effectively by using only single soft computing technique.In this research, in the first step, the possibility of predicting stock price of National Iranian Copper Industries Company wasstudied. Then, for predicting of stock price after one day neural ¬network of MLP by learning algorithm of Levenberg-Marquardt were used. Then optimize structure of neural network was trained with the standard BP algorithm, the learningrate is 3/0 has the best performance. And for this learning rate, sensitive of standard BP algorithm was calculated to minimizelocal. At the end, standard BP algorithm with momentum is used. The results showed that predicting by standards BPalgorithm with momentum is better than the standard BP algorithm. Manuscript profile