Progressive developments in economics, society and politics have raised knowledge as a key element in development and competitiveness, and knowledge management is considered to be an essential element in this field. By taking the temporary nature of the project into account, dynamics and competitiveness in Project-oriented organizations within the business world make the preservation and management of knowledge in project-based organizations more important. The lesson learned system is a knowledge management tool that proposes strategic solutions that avoid wasting time and money and makes perfect use of knowledge management accomplishments.Lessons learned (LL) systems have been deployed in many military, commercial, and government organizations to disseminate validated experiential lessons. They support organizational LL processes, and implement a knowledge management (KM) approach for collecting, storing, disseminating, and reusing experiential working knowledge that, when applied, can significantly benefit targeted organizational processes. An effective lesson learned process can substantially improve decision processes, thus, representing an essential chapter in knowledge sharing and knowledge management. Unfortunately, these systems typically fail to deliver lessons when and where they are needed.In this study, using a literature review, interviews and a case study, a roadmap for implementing the lesson learned system is explained in four stages. First, we illustrate the lesson learned and the learning in the project using a literature review. Second, we detail an understanding of commonly used methods in Iran obtained from two information sources; 1) interviews 2) a case study. Third, the information is analyzed and a conceptual model is developed based on the content analysis of data obtained in the second stage. Finally, we develop a roadmap by identifying key issues in the third stage and by adding activities and checklists to pursue its activities.This project learning roadmap assists business leaders in improving the lesson learned process. This model enables organizations to develop exclusive solutions tailored to the needs of the stakeholders.

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Introduction system of landform classification for soil mapping has been desired by soil scientists in Canada for a long time. The Canada Soil Survey Committee (CSSC) adopted a system at a meeting held at the University of Guelph in February 1976. Many aspects of the system came from mapping schemes used by the Geological Survey of Canada for mapping surficial geology. The system also embodies concepts developed initially by R.J. Fulton and later by N.F. Alley while doing terrain mapping in British Columbia. However, the needs of the soil scientist for a terrain or landform classification system are not necessarily compatible with those of the geologist. Relief analysis is a tool to analyse a landscape based on a Digital Elevation Model (DEM). One of the simplest parameters might be the elevation itself, or slope or the exposition of a given point in a landscape. Moore et al. (1991) state that the spatial distribution of topographic attributes can often be used as an indirect measure of the spatial variability of hydrological, geomorphologic and biological processes. The advantage compared to other information such as soil parameters or biomass production estimates is based on the relatively simple and fast techniques to model processes in large areas and the complex spatial patterns of environmental systems as seen by Moore et al. (1993b). Another relief parameter relevant for this work is landforms or relief units. Each of these contains certain characteristic physical, chemical, and biological processes and parameters (see Dehn et al., 2001). Milne (1936) was one of the first scientists, who recognised the catena principle of soil formation in a hilly terrain (Ruhe, 1960).Material And Methods Materials are classified according to their essential properties within a general framework of their mode of formation. Four groups (components) of materials have been recognized to facilitate further characterization of the texture and the surface expression of the materials. They are unconsolidated mineral, organic, consolidated, and ice components. These groups and the classes established within them are presented below. This research is trying to classify landforms on the basis of self-organizing neural network algorithm (SOM) in the watershed Gavkhoni pay to use the SOM algorithm is used to classify landforms of 6 parameters that includes orientation (aspect), height (elevation), tilt (slope), the longitudinal and transverse profiles (plan, profile) and curvature (curvature) is.Generally, The aim ofthisstudyis theclassificationof landformsin thebasinGavkhoni. Classification methodstohelpmajorlandformsvisitthe field, usingtopographic mapsandaerial photos, which requires experience. Theautomaticmethodbased ondigital elevation model(DEM)can beusedto classifylandformsBasinGavkhoni. Result And discussion The results of the classification of landforms using SOM algorithm showed that 6 cluster (class) in the study area there as clusters 1 and 5 includes landforms that are at high altitudes and cluster 3 includes landforms that are located at the lowest height. The rest of the cluster, including the landforms that the average height of the watershed studied. So the algorithm can be used to predict the landforms of the study area. The results showed that6isthe maximumdatain SOM algorithm. Also, at leastinthishexdatais zero, which indicates thatthere areno numbersinthislocation. The results ofprincipal component analysisshowedhigh densityanddistributiondata. According to theabove resultsshow thatthelandformsinput datain Figure6 classeshave beendistributedin the study area.Conclusion In this research was used SOM (SOM) to classify landforms. In order to use algorithms for classification of landforms of 6 parameters were used in the watershed Gavkhoni, The results of the classification of landforms using SOM algorithm showed that 6 cluster (class) in the study area ther. as clusters 1 and 5 includes landforms that are at high altitudes and cluster 3 includes landforms that are located at the lowest height. While cluster 3 includes landforms that are the lowest height. The rest of the cluster, including the landforms that the average height of the watershed studied. In general, using the SOM algorithm can be 6 classes to classify landforms in the study area predicted. Using the results of the SOM algorithm to manage watershed management approaches should be considered 6.

Ethical behaviors and ethical values are important issues in many researches related to business ethics. Ethical basis of all values in organization is ethical values. These values contribute to establishment and sustenance of standards which can be influential in leading people to initiatives which are favorable to organization. In particular the organization success has increased once the standards or the organization ethical values are wide spread among its members. In this article it is attempted to study the organization ethical values consequences and their interrelations (organization equality, organization commitment, organization behavior and organization citizenship behaviors). The results of this research showed that the organization ethical values have positive influence on equality process and equality distribution. Equality process and equality distribution also have positive influence on employees organization commitment. organization commitment also has positive influence on employee ethical behavior. Ethical behavior has also positive influence on organization citizenship behavior philanthropic and manliness dimensions.

Increasingly speed of technological changes in one hand and the change in the nature of customers ’demands and the competition intensity among organizations on the other hand have caused organizations to be in search of new competitive advantages over rivals and better supply of customers demands. It seemed that the movement towards the establishment of organizations which are highly flexible and speedy in response to changing, unsustainable and unpredictable environment is a new and critical solution in this issue. Achievement of such targets is resulted in the light of new concept of organization agility. Therefore this article is intended to determine the value and the significance of organization agility as pivotal axis of organization flexibility and responsion speed against established changes. Thus the theoretical bases of organization flexibility and responsion speed are deeply investigated. Based on the results of this research, traditional organizations cannot respond timely to customers’ demands and surrounding changes and developments. Then the continuation of their life will be impossible. Research and investigation in different sources also indicated that the learning organizations and virtual organizations are among organizations which due to having characteristics of agile organizations can better and faster adjust to surrounding environments through remaining in competition arena.