Development of an expert system to assist in Resource Management

© 2014 IEEE. This paper aims to demonstrate an idea of utilizing Kohonen Maps as a tool to portray and study resource allocations when constructing an expert system to assist in Resource Management. The context of work encompasses resource allocation and management tasks related to design of courses, as well as, various teaching and learning projects. The key aspect is to show the design of an expert system for resource allocation with the use of Kohonen Maps as an alternative way to visualise the demand and availability of project resources

The development of an expert system for decision making in forest resources management.

Tropical forests are a repository of biodiversity which provides habitats for more than 50% of the earth, s plant and animal species, an important sink for carbon stores which provides many goods and ecosystem services and a critical contributor to livelihoods, mainly of the indigenous groups which are totally dependent on forests. Yet, forests are under pressure. Tropical forests are among the earth, s most threatened ecosystems, particularly threatened by human activities and climate change. Consequently, tropical forests are loosing capacity to provide basic goods and services that are essentials to human livelihood. Hence, every decision involving forest utilization should consider various criteria that are important for sustainable forest management. However, making decision about forest resources management often involves balancing conflicting, inadequate and incompatible values of many users and usage of a resource. One of the most fundamental and difficult task is the effective integration of environmental, economic and social values to achieve and maintain ecologically sustainable development. Therefore, an integrated technology such as an Analytical Hierarchy Process and expert systems is essential to be performed in making decision process for forest resources management because an AHP method is capable to capture both tangible and intangible criteria. This study places emphasis on the development of expert system for forest resources management to assist decision makers to select the best forest resources use based on Malaysian Criteria and Indicators [(MC&I)2002]

Interactive Energy Demand Analysis: The MAED-BI Model Application in the Shanxi Province, PRC

The decision support system described in this report combines several data bases, simulation and optimization models, and AI components, in an easy-to-use Expert System framework. A graphical and largely symbolic user interface, relying exclusively on menu techniques and providing help and explain functions, makes access to the system's functions easy for the planner and decision maker, who might have little or no computer experience. The system is designed to assist the five-year planning process in Shanxi Province, which in the Chinese philosophy of integrated development, includes investment distribution, i.e., primarily economic, but also technological, resource, environmental and socio-political considerations. The scope of the system ranges from the macroeconomic level down to sectoral and engineering-oriented models. Modeling in in the Shanxi software system is done with the help of the MAED-BI (Model for Analysis of Energy Demand in Basic Industries). This model, which centers on heavy industry, has been extended to cover the full range of economic sectors for compatibility with the overall system. Connection to a relational data base management system for the definition of input scenarios, and an interactive, graphical user interface for the selective display are important features of this model

The development of an expert system for decision making in forest resources management.

Tropical forests are a repository of biodiversity which provides habitats for more than 50% of the earth, s plant and animal species, an important sink for carbon stores which provides many goods and ecosystem services and a critical contributor to livelihoods, mainly of the indigenous groups which are totally dependent on forests. Yet, forests are under pressure. Tropical forests are among the earth's most threatened ecosystems, particularly threatened by human activities and climate change. Consequently, tropical forests are loosing capacity to provide basic goods and services that are essentials to human livelihood. Hence, every decision involving forest utilization should consider various criteria that are important for sustainable forest management. However, making decision about forest resources management often involves balancing conflicting, inadequate and incompatible values of many users and usage of a resource. One of the most fundamental and difficult task is the effective integration of environmental, economic and social values to achieve and maintain ecologically sustainable development. Therefore, an integrated technology such as an Analytical Hierarchy Process and expert systems is essential to be performed in making decision process for forest resources management because an AHP method is capable to capture both tangible and intangible criteria. This study places emphasis on the development of expert system for forest resources management to assist decision makers to select the best forest resources use based on Malaysian Criteria and Indicators [(MC&I)2002]

Interactive Energy Demand Analysis: A Case Study of Shanxi Province, PRC

Within the framework of collaboration between IIASA's Advanced Computer Applications project (ACA) and the State Science and Technology Commission of the People's Republic of China (SSTCC), ACA has developed an integrated set of information and decision support system for development planning in China. The system is implemented for a case study of Shanxi, a province in north central China, which is very rich in coal and several mineral resources, but is still at an early stage of development, lacking, for example, a well developed infrastructure, or sufficient water. The decision support system combines several data bases, simulation and optimization models, and AI components, in an easy-to-use Expert System framework. A graphical and largely symbolic user interface, relying exclusively on menu techniques and providing extensive help and explain functions, makes access to the system's functions easy for the planner and decision maker, who might have little or no computer experience. The system is designed to assist the five-year planning process in Shanxi Province, which, in the Chinese philosophy of integrated development, includes investment distribution, i.e. primarily economic, but also technological, resource, environmental, and socio-political considerations. The scope of the system, consequently, ranges from the macroeconomic level down to sectoral and more engineering-oriented models. The energy sector certainly plays one of the most important roles in Shanxi's economic development. Shanxi is China's power house: with annual coal production approaching 250 Mt, economic and industrial development is centered around the production and use of coal. In the Shanxi software system, modeling the energy demand (and also related investment, labor, and water requirements) of planned production schemes, or more generally, the economic and social development, is done with the help of the MAED-BI (Model for Analysis of Energy Demand in Basic Industries). While centered on heavy industry, the model has been extended to cover the full range of economic sectors for compatibility with the overall system. Connection to a relational data base management system for the definition of input scenaria, and an interactive, graphical user interface for the selective display of model results, are important features. The model was developed in collaboration with the International Atomic Energy Agency (IAEA), and is based on previous work done at IIASA's Energy Program. It is not only a valuable component in the overall software system, but also provides an example of the model-based decision support philosophy that is at the core of the overall project

Planning and Resource Management in an Intelligent Automated Power Management System

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process

Developing STEM Identity of Nez Perce Students: Identifying Entry-Level Competencies for Forestry and Fire Management

The purpose of this study was to identify the competencies that are required for entry-level forestry and fire management technicians. The strategy is a part of a larger goal to develop the STEM identity of Nez Perce students through the integration of relevant competencies in middle and high school curriculums. The DACUM process was used. Through this groupware process, nine experts from the Nez Perce Natural Resources produced a competency profile consisting of 12 duties and 79 tasks, along with general knowledge and skills, attitudes, tools, and future trends. Findings indicate that the experts view relevant cultural competencies as central to the function of the job and not as mere enablers. This has implications for how content is integrated, taught, and assessed in schools

End-of-life vehicle (ELV) recycling management: improving performance using an ISM approach

With booming of the automobile industry, China has become the country with increasing car ownership all over the world. However, the end-of-life vehicle (ELV) recycling industry is at infancy, and there is little systematic review on ELV recycling management, as well as low adoption amongst domestic automobile industry. This study presents a literature review and an interpretive structural modeling (ISM) approach is employed to identify the drivers towards Chinese ELV recycling business from government, recycling organizations and consumer’s perspectives, so as to improve the sustainability of automobile supply chain by providing some strategic insights. The results derived from the ISM analysis manifest that regulations on auto-factory, disassembly technique, and value mining of recycling business are the essential ingredients. It is most effective and efficient to promote ELV recycling business by improving these attributes, also the driving and dependence power analysis are deemed to provide guidance on performance improvement of ELV recycling in the Chinese market

An intelligent linked data quality dashboard

This paper describes a new intelligent, data-driven dashboard for linked data quality assessment. The development goal was to assist data quality engineers to interpret data quality problems found when evaluating a dataset us-ing a metrics-based data quality assessment. This required construction of a graph linking the problematic things identified in the data, the assessment metrics and the source data. This context and supporting user interfaces help the user to un-derstand data quality problems. An analysis widget also helped the user identify the root cause multiple problems. This supported the user in identification and prioritization of the problems that need to be fixed and to improve data quality. The dashboard was shown to be useful for users to clean data. A user evaluation was performed with both expert and novice data quality engineers