Expert System For Planning Research Articles

GREEN PATH: an expert system for space planning and design by the generation of human trajectories

Public space is usually conceived as where people live, perceive, and interact with other people. The environment affects people in several different ways as well. The impact of environmental problems on humans is significant, affecting all human activities, including health and socio-economic development. Thus, there is a need to rethink how space is used. Dealing with the important needs raised by climate emergency, pandemic and digitization, the contributions of this paper consist in the creation of opportunities for developing generative approaches to space design and utilization. It is proposed GREEN PATH, an intelligent expert system for space planning. GREEN PATH uses human trajectories and deep learning methods to analyse and understand human behaviour for offering insights to layout designers. In particular, a Generative Adversarial Imitation Learning (GAIL) framework hybridised with classical reinforcement learning methods is proposed. An example of the classical reinforcement learning method used is continuous penalties, which allow us to model the shape of the trajectories and insert a bias, which is necessary for the generation, into the training. The structure of the framework and the formalisation of the problem to be solved allow for the evaluation of the results in terms of generation and prediction. The use case is a chosen retail domain that will serve as a demonstrator for optimising the layout environment and improving the shopping experience. Experiments were assessed on shoppers’ trajectories obtained from four different stores, considering two years.

A Rule-Based Expert System for Efficient Food Planning and Consumption

Proper food planning is essential to consume nutritious food that keeps people healthy. Hygienic food offers a favorable existence that helps us to cut the chance of illness and to save time in selecting food. Food planning may ensure a new way to change our buying nature as well as bring variation in our food consumption. Selecting the right food at the right time is necessary. This paper presents an expert system that is intended to select the right food for the right meal for any age people. The expert system also suggests the amount of energy in Kcal required per day. We use rule rule-based expert system to carry out the system. The knowledge base, inference engine, and user interface are combined to give the service. This system helps us to cut the amount of food wastage as well as gives the proper nutritious diet.

Application of Capital Market Investment Planning Expert System Using Website-Based Forward Chaining Method

Good investment planning is the beginning to achieve investment goals. Price fluctuations in the capital market and financial behavior are the guides for the community in making investment plans. The low level of financial literacy in the community causes people to more often forget to make investment plans and if they are made only based on feelings. Thus, it is necessary to have a system that helps the community to make effective investment plans. The expert system was chosen for that because it has everything needed to meet these needs. In this study, the expert system uses the forward chaining method. After developing the expert system, it runs well and can meet the needs of the community.

A stochastic approximation approach to spatio-temporal anchorage planning with multiple objectives

Globalization and subsequent increase in seaborne trade have necessitated efficient planning and management of world’s anchorage areas. These areas serve as a temporary stay area for commercial vessels for various reasons such as waiting for passage or port, fuel services, and bad weather conditions. The research question we consider in this study is how to place these vessels inside a polygon-shaped anchorage area in a dynamic fashion as they arrive and depart, which seems to be the first of its kind in the literature. We specifically take into account the objectives of (1) anchorage area utilization, (2) risk of vessel collisions, and (3) fuel consumption performance. These three objectives define our objective function in a weighted sum scheme. We present a spatio-temporal methodology for this multi-objective anchorage planning problem where we use Monte Carlo simulations to measure the effect of any particular combination of planning metrics (measured in real time for an incoming vessel) on the objective function (measured in steady state). We resort to the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm for identifying the linear combination of the planning metrics that optimizes the objective function. We present computational experiments on a major Istanbul Straight anchorage, which is one of the busiest in the world, as well as synthetic anchorages. Our results indicate that our methodology significantly outperforms comparable algorithms in the literature for daily anchorage planning. For the Istanbul Straight anchorage, for instance, reduction in risk was 42% whereas reduction in fuel costs was 45% when compared the best of the current state-of-the-art methods. Our methodology can be utilized within a planning expert system that intelligently places incoming vessels inside the anchorage so as to optimize multiple strategic goals. Given the flexibility of our approach in terms of the planning objectives, it can easily be adapted to more general variants of multi-objective spatio-temporal planning problems where certain objects need to be dynamically placed inside two or even-three dimensional spaces in an intelligent manner.

Automated Discovery and Utilization of Tacit Knowledge in Facility Layout Planning and Optimization

This paper puts forth a novel methodology for facilities layout planning and optimization, where the fitness evaluation of layout alternatives is automatically performed by employing an artificial neural network trained to preferences of the domain experts. The inherently uncertain, unstructured, and often tacit nature of facilities layout design preferences, constraints, and fitness objectives demands the use of domain experts for the fitness evaluation of layout alternatives, which is a resource-intensive process. Indeed, the usual unavailability of domain experts in a timely or economical manner highlights the need for resorting to the use of some intelligent and effective automation technique in this important domain. In order to test the key novel ingredient of the proposed approach, a variety of artificial neural networks are trained on a large data set containing both qualitative and quantitative fitness values of layout alternatives, as well as subjective rankings by a seasoned domain expert utilizing the knowledge of the application domain. Simulation results strongly support the viability of the proposed idea. Such an automated approach to fitness evaluations of layout alternatives is expected to significantly increase the efficacy and efficiency of the overall facilities layout planning process. Moreover, such an approach would spur the much sought for research in decision support and expert systems in layout planning. As such, the paper also provides some very interesting and promising, albeit challenging, future research directions.

A causal knowledge-based expert system for planning an Internet-based stock trading system

This study describes a causal knowledge-based expert system for planning an Internet-based stock trading system, abbreviated CAKES-ISTS. The case base of this system consists of the qualities that promote ISTS use, two specific facets of ISTS use (stock amount purchased and frequency of use), and user satisfaction. Planning ISTS requires consideration of the complex causal relationships between system qualities, system use, and performance (i.e., user satisfaction). This study also examines the factors affecting the level of system usage and performance. First, this study uses a fuzzy cognitive map (FCM) to develop the causal knowledge base of the expert system for ISTS planning. Second, this study uses structural equation modeling to estimate the relevant relationships among FCM components as well as their direction and strength. Third, this study develops rules based on system qualities to predict the usage and performance level of ISTS, allowing the identification of the qualities essential to enhance system usage and performance. This clearly shows how effective ISTS planning is possible through the inference process provided by CAKES-ISTS.

Apply 3C Theory in Collaborative Planning, Forecasting, and Replenishment Expert System Formulation

In recent years, both the VICS CPFR committee and ECR Europe have published several reports presenting pilot implementations of the CPFR process model and providing recommendations and roadmaps for companies interested in implementing it. These sources indicate that by implementing CPFR both retailers and suppliers can expect to benefit from increased forecast accuracy, reduced stock-outs, increased sales, and reduced inventories. Based on the commonality, capacity and consumption (3C Theory) of a specific material, a GARCH based collaborative planning, forecasting, and replenishment (CPFR) expert system associated with 3C Theory is proposed in this paper. Meanwhile, through setting an optimal safety multiplier in exception policy, an exception demand also can be efficiently and effectively controlled to maximize the net present value. Keyword: Collaborative Planning, Forecasting, Replenishment (CPFR), GARCH Model, Expert System, 3C Theory

Forest management planning expert system for wildfire damage reduction

Forest ecosystems provide a variety of goods as it is, for example, firewood, technical timber, fruits and roots of plants. They also accord important indirect benefits, as is flood protection and atmospheric pollution reduction. Despite their importance, they face systematically the danger of shrinkage in many parts of the planet. To face this problem, this paper describes all the phases for the development of an Expert System that provides consultation for Forest Management Planning and for the reduction of the Wildfire Destruction Danger. Its implementation makes use of a Fuzzy Logic, for the handling of uncertainty, and a rule-based knowledge base. The software developed has carefully tested and evaluated by three distinct groups of users, including potential end-users, with satisfactory results.

A MCDM-based expert system for climate-change impact assessment and adaptation planning – A case study for the Georgia Basin, Canada

An MCDM-based expert system was developed to tackle the interrelationships between the climate change and the adaptation policies in terms of water resources management in the Georgia Basin, Canada. User interfaces of the developed expert system, named MAEAC (MCDM-based expert system for adaptation analysis under changing climate), was developed based on system configuration, knowledge acquisition, survey analysis, and MCDM-based policy analysis. A number of processes that were vulnerable to climate change were examined and pre-screened through extensive literature review, expert consultation and statistical analysis. Adaptation policies to impacts of temperature increase, precipitation-pattern variation and sea-level rise were comprehensively explicated and incorporated within the developed system. The MAEAC could be used for both acquiring knowledge of climate-change impacts on water resources in the Georgia Basin and supporting formulation of the relevant adaptation policies. It can also be applied to other watersheds to facilitate assessment of climate-change impacts on socio-economic and environmental sectors, as well as formulation of relevant adaptation policies.

Expert systems in land-use planning: An overview

This paper presents a state-of-the-art review of the use of expert systems in land-use planning in general and site selection in particular. It focuses on the theoretical discussion of different types of computer-based systems (i.e. expert systems, decision support systems, integrated systems) and tries to assess the usefulness of each system for the urban planner.

A cooperative expert system for transmission expansion planning of electrical power systems

This paper describes a cooperative expert system for managing the transmission expansion planning process, taking into account the selection of feasible transmission routes, as well as the definition of the expansion plan itself. The use of an expert system is proposed to create a planning environment, which can not only emulate the human expert reasoning, but also represent appropriately all heuristic knowledge related to this problem. The main point of this system is the fact that it is able to define feasible alternatives for the expansion of the electrical transmission system. Afterwards, the expert system executes a network flows program, which determines the minimum cost expansion plan. The developed prototype is tested with a realistic system of 500 busbars.

A process planning expert system based on a flexible digit length coding scheme

This paper introduces a generative process planning expert system based on a flexible digit length coding scheme which has been developed specifically for the automated generation of process plans for manufacturing prismatic components. The structure of modules required for the formation of a Generative Computer Aided Process Planning Expert System (GCAPPES), which is aimed at interfacing with the various process planning functions and interrelated manufacturing systems so as to capture and maintain the manufacturing knowledge of process planning for machining prismatic components, has been presented. It is basically a rule-based program that recognizes a new group technology (GT) coding scheme and creates a process plan that includes a list of operations, sequences, machines, cutting tools and parameters such as cutting speed, feed rate and depth of cut. A prototype program has been built and tested with results that proved the feasibility of this new GT coding scheme combined with an expert system for generating process plans in prismatic components manufacturing.

A proposal of a supporting expert system for outage planning of electric power facilities retaining high power supply reliability

It is necessary for a power system to undertake maintenance works regularly to secure stable power supply, which inevitably cause outage of associated apparatus. This problem, referred to as the outage planning of an electric power system in this paper, has been so far made based on the knowledge and experiences of planning engineers. However, the scheduling made by the engineers is not necessarily optimal since there are no rational criterion to judge the results. Furthermore, this problem belongs to a class of combinatorial optimization problems. Therefore, we propose a supporting expert system for the outage planning retaining high power supply reliability. This paper presents some issues on the outage planning and an outline of the proposed supporting system. The concept of work unit is introduced and three security indices are utilized to properly merge several related outage work into the same group.

A proposal of a supporting expert system for outage planning of electric power facilities retaining high power supply reliability. II. Knowledge processing and simulation results

For pt.I see ibid., vol.13, no.4, p.1453-8 (1998). A prototype system has been constructed to validate the proposed method for assisting outage work scheduling that has been described in part I. The prototype system has the following three functions: (1) to identify outage areas to be caused by requested outage works, (2) to generate a work unit into which as many outage works as possible should be merged, and (3) to schedule work units and to determine a suitable system configuration to assure a high supply reliability. In order to realize these functions, it is necessary to deal with demands of planning engineers for improving power system security as well as some constraints such as the number of available workers and ordering among outage works. Therefore, knowledge processing is mandatory since these factors are difficult to formulate in conventional procedure oriented languages. The proposed system has been successfully applied to test cases with 50 outage work requests taken from a part of the 110 kV transmission line system. Results obtained have made clear the superiority of the proposed method to the current scheduling based on just the experience of the maintenance engineers.

グラインディングセンタによる研削加工の工程設計用エキスパートシステムの開発

グラインディングセンタによる研削加工の工程設計用エキスパートシステムの開発

Application of a Case-Based Expert System to Orthodontic Diagnosis and Treatment Planning: A Review of the Literature

Abstract Computer expert systems are being utilised increasingly in medical fields to assist diagnosis and treatment planning. Traditional rule-based expert systems have some limitations when applied to orthodontic diagnosis and treatment planning. These limitations may be avoided by using a case-based system which is a particular type of expert system that uses a stored data bank of previously-treated cases to provide the knowledge for solving new treatment problems. This article reviews the use of expert systems for orthodontic diagnosis and treatment planning, outlines the rationale, processes and advantages of case-based systems, and gives examples of the application of this technology in medical fields.

The role of common sense knowledge in menu planning

Planning nutritious and appetizing menus is a task at which experts consistently outperform computer systems, making it a challenging domain for AI research. This paper describes lessons learned through the sequential construction of four expert systems for menu planning. The first of these systems, ESOMP (Expert System on Menu Planning), was built to plan menus for patients on severely restricted low protein diets. A need for common sense in structuring “sensible” looking meals was identified and addressed via meal patterns and food exchange groups. PRISM (Pattern Regulator for the Intelligent Selection of Menus) expanded upon ESOMP by planning menus to meet a broad range of dietary requirements and personal preferences. Simple knowledge representation structures, implemented in PRISM 1.0, proved inadequate for the expanded task. A hierarchical network structure was developed and implemented in PRISM 2.0 and PRISM 3.0. This structure captures the common sense concept of menu form and describes context-sensitive relationships among menu parts. A major contribution of this paper is showing how to represent common sense knowledge about food and menus in a form amenable to successful menu planning.

A review of knowledge-based expert systems for process planning. Methods and problems

This paper presents a review of knowledge-based expert systems for process planning and related methods and problems. It is based mainly on literature and partially on a questionnaire investigation carried out by the author. After a general presentation of process planning, the main problems are classified and the related methods and approaches for solving them are discussed. Finally, a list of fifty-two prototype systems is presented and their main characteristics are summarised in two tables.

Knowledge-Based System for Construction Planning of High-Rise Buildings

The knowledge-based expert system for construction planning is part of an automated building realization process. The system uses an object-oriented representation of the building and production rules, routines, and functions to manipulate objects and to generate the construction plan. The building is represented by its zones, functional systems, and works. The procedural knowledge employs rules for the generation of activities and their dependences. The algorithms are employed to allocate resources and to generate the construction schedule. The algorithms reflect the different objectives of managerial decision making, such as least cost, managerial efficiency, or fastest completion. This paper presents the principles of the system, explains the structure of its knowledge base, and discusses various implementation aspects. It also includes an example of the application.

The implementation of an integrated transportation planning model with GIS and expert systems for interactive transportation planning: Choi, Keechoo, Ph.D. University of Illinois at Urbana-Champaign, 1993. 235 pp. adviser: Tschangho John Kim

The implementation of an integrated transportation planning model with GIS and expert systems for interactive transportation planning: Choi, Keechoo, Ph.D. University of Illinois at Urbana-Champaign, 1993. 235 pp. adviser: Tschangho John Kim