Expert System Using Fuzzy Logic Computer Science Essay

This paper describes the suitableness of application of expert system utilizing Fuzzy Logic ( FL ) engineering in agribusiness and proposes the development of a rule-based expert system, named SITAPAL ( It is Hindi Language Word and it means Custard Apple ) , for the efficient direction of the custard apple. The proposed system uses the cognition of ocular lack symptoms, evident in the workss, to name the foods deficiency/excess in the custard apple harvest. This system has been developed in the Microsoft VB.Net environment. The ocular lack symptoms of all the indispensable elements have been included in the cognition base of the expert system. The system first finds out the deficiency/excess of foods in the dirt and so recommends the name of suited fertiliser taking in consideration some chemical belongingss of the dirt. The consequences given by the system have been found to be consistent and sound. However, the diagnosing consequence has been found to be more accurate in the instance of sever lacks.

Keywords: expert system ; knowledge base ; Fuzzy Logic ; Visual Basic.Net

I INTRODUCTION

Adept Systems is one of the of import application oriented subdivisions of Artificial Intelligence in last two decennaries, a great trade of adept systems had been developed and applied to many Fieldss such as office mechanization, scientific discipline, medical specialty and agribusiness. All of us straight or indirectly depend on agribusiness from where come trade goods to feed the life existences. In the underdeveloped states like India, Pakistan, Bangladesh, Israel, Egypt and African states, agribusiness is the business of major part of population. However, agricultural patterns are more manual and technically non-advanced in comparing to developed states.

The possible benefits of using adept systems to agriculture direction have been identified for several old ages. The yearss of printed notes are gone and computing machine based solutions are welcomed. The production of harvest depends on so many factors like birthrate of the dirt, type of seed, climatic status, H2O logging, application of fertilisers, plague and disease control etc. For better outputs every factor requires proper planning and direction that in bend demands right determination doing from husbandmans based on information and cognition obtained from different related countries. Fuzzy systems are an alternate to traditional impressions of set rank and logic that has its beginnings in ancient Grecian doctrine, and applications at the taking border of Artificial Intelligence.

Yet, despite its long-standing beginnings, it is a comparatively new field, and as such foliages much room for development.

2 ROLE OF EXPERT SYSTEMS IN AGRICULTURE

Expert system evolved as first commercial merchandise of Artificial Intelligence and is now available in big figure of countries specially related with decision-making. The rightness of this engineering has besides been recognized and realized in the field of agribusiness and several successful systems have been developed. The modern clip agribusiness requires information and application of cognition from different interacting Fieldss of scientific discipline and technology to make allow decision-making that in bend depends on interplay of this information and cognition.

3. SITAPAL EXPERT SYSTEM ARCHITECTURE & A ;

Development

Rule based scheduling is one of the commonly used techniques to develop adept system and the same has been used in the present work excessively.

A typical rule-based expert system integrates a job sphere specific cognition base, an illation engine and the user interface. The system is capable in utilizing its internal cognition and regulations to explicate its ain solution process based on job definition. The proposed system has the following four functional faculties:( I ) Knowledge base( two ) Inference engine( three ) Intelligent User ‘s interface( four ) Explanation facultyThe interconnectedness and agreement of these faculties is shown in Fig.1. The present system has been developed in the ocular basic environment, which works as an illation engine in backward chaining. The development procedure of the expert system is really systematic and can be carried out in different phases The whole procedure followed has been presented in the flow chart diagram shown in the Fig.2. The Knowledge Base of the present system consists of two faculties.

First faculty of the cognition base for designation plague and other is for urging appropriate pesticide.

Figure 1: Interconnection between faculties

4 HOW IS FL USED IN THIS SOFTWARE

We defined the control aims and standardsDetermine the input and end product relationships and take a minimal figure of variables for input to the FL engine ( typically error and rate-of-change-of-error ) .Using the rule-based construction of FL, interrupt the control job down into a series of IF X AND Y THEN Z regulations that define the coveted system end product response for given system input conditions. The figure and complexness of regulations depends on the figure of input parametric quantities that are to be processed and the figure fuzzed variables associated with each parametric quantity. If possible, usage at least one variable and its clip derivative. Although it is possible to utilize a individual, instantaneous mistake parametric quantity without cognizing its rate of alteration, this cripples the system ‘s ability to minimise wave-off for a measure inputs.

Create FL rank maps that define the significance ( values ) of Input/Output footings used in the regulations.Test the system, measure the consequences, tune the regulations and rank maps, and retest until satisfactory consequences are obtained.

5. DOMAIN KNOWLEDGE

The cognition acquisition is most of import portion of this undertaking. It done for the proposed system from two beginnings viz. human expert and by reaping the utile cognition from the standard mentions.

Attempts have been made to roll up more and more heuristic cognition to place the plagues based on lack symptoms. The lack symptoms related harvest have been included.The undermentioned information is collected from a sphere cognition individual.Custard Apple ( Annona Squamosa ) , Popularly known as “ Sitaphal ” in southern side of India. The mature fruit is really delightful and nutritionally valuable with 20-22 % sugars. It is tropical beginning and can non stand hoar or prolonged cold periods. Fruits become difficult and make non mature in terrible cold conditions. It grows good in low to medium heights with warm winters and moderate summers.

The custard apple is by and large propagated by seed. But the workss obtained by seed extension differ markedly in fruit size, output and quality. Pits of 0.5 X0.5 X0.5 m are dug at 2-4m apart depending upon the dirt birthrate.

Two baskets or 20kg FYM and 300g ace phosphate are incorporated at the clip of make fulling the cavity.

6 Execution

Fig 2.0: Welcome screen to the expert systemFig 3.0: Main MenuThe above is chief entry screen. The user can choose the option to voyage the expert system.

The screen shows the assorted faculties of the system. The faculties are Planting, Climatic and dirt demands, Plagues and Diseases, Harvesting, Yield and Ripening, About Custard Apple, and Marketing Opportunities.Fig 4.0: Planting Information SystemThe above screen is demoing the faculty planting. When the user chooses the present season is Autumn and inquiring the consequence to get down the plantation the system is reacting with reply “ NO ” . If the user asks the inquiry why? It shows as “ THE CUSTARD APPLE PLANATION IS NOT POSSIBLE IN AUTUMN SEASON.

Fig 5.0: Expert Advices about the SitapalAll the above all faculties are prepared. Because of the deficiency of infinite here, we are non demoing the consequences. This package is free package. It will be kept on the web. The web portal is www.vaisesika.

info. Choose the downloads and you can happen the complete information.

7 Decision

Integrating Fuzzy logic and Expert Systems under a incorporate model in agribusiness sphere is really of import undertaking specially in scheduling system like Agriculture This paper presents an Expert system utilizing fuzzed logic.

This system provides a hierarchal representation of the job work outing methods, undertakings and crude job work outing methods ( inference measure ) . It besides contains generic sphere cognition, i.e. the portion of the sphere cognition that can be reused in other similar agribusiness scheduling systems without alteration. This system besides helps the cognition applied scientist to construct a new simpler, quicker and more effectual system, and recycling the already bing constituents in similar systems. The developers can bring forth or update their systems to include the turning expertness and techniques.

The system is in beta testing and many husbandmans expressed their positions. We are welcoming your positions to better the sustainability of agribusiness in developing states. The future range of this system is to develop system with local linguistic communications of India like Telugu, Hindi and other.