基于深度学习的CLIPS进行园艺疾病和害虫诊断内含数据集和运行说明.zip

# clips-horticulture-expert-system A Knowledge Based System (KBS) using CLIPS for Horticulture disease and pest diagnosis that __automatically generates rules__ from a .txt file. Read more about the [automation](#automated-query-rules-for-specific-symptoms) View the data about the symptoms from the [symptoms documentation](https://github.com/wcyn/clips-horticulture-expert-system/blob/master/symptoms.md) ## How to run this program Clone the repo: ``` git clone https://github.com/wcyn/clips-horticulture-expert-system ``` Run the [CLIPS Program](https://sourceforge.net/projects/clipsrules/):  Click on File -> Load, then browse to the directory with the cloned files.  Click on `diagnosis_rules_automated.CLP` file. Then click Open. On the CLIPS command line, type: ``` CLIPS> (run) ``` ## Table of Contents [How the Weights Work](#how-the-weights-work) [Template Definitions](#template-definitions)  [`deftemplate symptom-details`](#deftemplate-symptom-details)  [`deftemplate disease-weight`](#deftemplate-disease-weight) [Function Definitions](#function-definition)  [`deffunction ask-question`](#deffunction-ask-question)  [`deffunction yes-or-no-p`](#deffunction-yes-or-no-p)  [`deffunction which-plant`](#deffunction-which-plant)  [`deffunction diagnose-plant`](#deffunction-diagnose-plant) [Query Rules](#query-rules)  [`defrule determine-plant`](#defrule-determine-plant) [Automated Query Rules for Specific Symptoms](#automated-query-rules-for-specific-symptoms)  [`deffunction read-from-symptoms-file`](#deffunction-read-from-symptoms-file)  [`deffunction create-query-rules`](#deffunction-create-query-rules)   [`defrule determine-yellow-patch-leaves`](#defrule-determine-yellow-patch-leaves) [Diagnosis Rules](#diagnosis-rules)  [`deffunction create-check-diagnosis-rule`](#deffunction-create-check-diagnosis-rule)  [`deffunction create-diagnosis-rules`](#deffunction-create-diagnosis-rules) [Giving Advice](#giving-advice)  [`deffunction give-advice`](#deffunction-give-advice) ## How the weights work Each symptom has an assigned **certainty factor** (a number between `0` and `1`), which defines the **confidence level** of the prescence of the disease if the symptom is true. The certainty factors are merely opinions and are therefore not supported by statistical evidence. For example, Rose Rust has four symptoms: - yellow-patch-leaves (certainty factor: 0.4) - orange-spores-leaves (certainty factor: 0.5) - leaves-fall (certainty factor: 0.3) - plants-defoliated (certainty factor: 0.6) As such: - yellow-patch-leaves `=>` rose-rust (by 0.4) - orange-spores-leaves `=>` rose-rust (by 0.5) - leaves-fall `=>` rose-rust (by 0.3) - plants-defoliated `=>` rose-rust (by 0.6) If `yellow-patch-leaves` and `leaves-fall` are set to true. Then we shall obtain a confidence level of the rose flower having rose-rust through a number of calculations: - `yellow-patch-leaves => not(rose-rust)` by a factor of 0.6 and `leaves-fall => not(rose-rust)` by a factor of 0.7 - `yellow-patch-leaves + leaves-fall => not(rose-rust)` by a factor of `0.6 * 0.7` = `0.42` - Which, after inverting gives us: `yellow-patch-leaves + leaves-fall => rose-rust` by a factor of `1 - 0.42` = **`0.58`** If we set the threshold to `0.7`, the diagnosis for rose-rust would fail. But if `orange-spores-leaves` symptom was also present, we would have a confidence factor of `(1 - (0.6 * 0.7 * 0.5)) = 1 - 0.21 = `**`0.79`**, and since `0.79 > 0.7`, the diagnosis for `rose-rust` would be true. ## Template Definitions These provide a framework to hold the various groups of data items. ### `deftemplate symptom-details` __Description__: Defines the types of data describing the details of a symptom __Slots__: -- `symptom-name` - Name of the Symptom -- `plant-name` - The name of the plant -- `disease-or-pest` - What disease or pest the symptoms belongs to -- `prescence` - If the symptom is present in the plant or not. Can be `yes` or `no`. Default is `no` -- `weight` - The weight that the symptom contributes to the overal disease or pest ### `deftemplate disease-weight` __Description__: Defines the name of the disease and the total weight it has after adding up all its symptom's weights __Slots__: -- `disease-or-pest-name` - Name of the disease or pest -- `plant` - Name of the plant that the disease belongs to -- `weight` - The total weight that the symptoms of the disease contribute. It's an addition of __only__ the present symptoms. ## Function Definitions ### `deffunction ask-question` __Description__: Asks a question __Arguments__: -- `question` - The question to ask the user -- `allowed-values` - Input values accepted for the question asked __Steps__: -- Printout the `question` -- Get user input and store it in `answer` -- If `answer` is not in `allowed-values`, keep asking the `question` -- Finally, return `answer` ### `deffunction yes-or-no-p` __Description__: Asks question and gets yes or no response from user __Arguments__: -- `question` - The question to ask the user __Steps__: -- Get yes or no response from user and store that in `response` -- Return `yes` if response is `yes` and `no` if response is `no` ### `deffunction analysis-mode` __Description__: Sets analysis mode to true or false. Analysis mode allows the user to see the calculations that lead to the diagnosis __Arguments__: -- `question` - Response by the user, `yes` or `no` __Steps__: -- Get response from user and change `analysis` gloabal variable to `TRUE` or `FALSE` accordingly. ### `deffunction which-plant` __Description__: Finds what plant is affected __Arguments__: -- `question` - The question to ask the user __Steps__: -- Get number / identity of plant affected from the user and store that in `response` -- Return `cabbage` if response is `1`, `banana` if `2` and so on.. ### `deffunction diagnose-plant` __Description__: Get weight totals of the group of symptoms for a disease or pest and give a positive diagnosis if threshold is exceeded __Arguments__: -- `plant-name` - The name of the plant -- `disease-or-pest` - What disease or pest the symptoms belongs to -- `threshold` - The total weight that must be exceeded for a certain disease or pest to be the accepted diagnosis __Steps__: -- Initialize the `weight` to zero -- Get all the weights of facts in the `symptoms-details` [template](#symptom-details) whose `prescence` is `yes`, `plant-name` is [argument specified for `plant-name`] and whose `disease-or-pest` is [argument specified for `disease-or-pest`] -- Add up those weights and assign them to `weight` b -- If `weight` is greater than [argument given for `threshold`], then return TRUE ## Query Rules ### `defrule determine-plant` __Description__: Determines the type of plant affected __Rule conditions__: Only fires if __no__ `diagnosis` has been reached, and __no__ `plant-name` has been provided by the user ## Automated Query Rules for Specific Symptoms Rules used to query the user about the various [symptoms](https://github.com/wcyn/clips-horticulture-expert-system/blob/master/symptoms.md) are automatically generated from the [`symptoms.txt`](https://github.com/wcyn/clips-horticulture-expert-system/blob/master/symptoms.txt) file. For all the rules to be generated, the function [`read-from-symptoms-file`](#deffunction read-from-symptoms-file) is called, which loops through the file extracting the data that is needed to create the rules. ### `deffunction read-from-symptoms-file` __Description__: Loop through the text file with the data and use the [`create-query-rules`](#deffunction-create-query-rules) function to create rules for each symptom __Arguments__: -- `template` - The [template](#template-details) to use for the details of the symptoms -- `file` - The name of the file containing the data