Aurora

🔍

question:Напиши экспертную систему на языке swi-prolog, которая будет рекомендовать пользователю напитки

answer:Для решения этой задачи следует создать базу знаний о виде напитков и их характеристиках. Например: drink(negroni, red, bitter, 23, strong, italian, cocktail, classic, gin, herbs). drink(margarita, yellow, sour, 15, refreshing, mexican, cocktail, classic, tequila, citrus). drink(mimosa, orange, fruity, 8, light, french, cocktail, brunch, prosecco, orange). drink(mojito, green, minty, 8, refreshing, cuban, cocktail, classic, rum, mint). drink(pina_colada, white, sweet, 12, creamy, caribbean, cocktail, tropical, rum, pineapple). drink(screwdriver, orange, sour, 11, easy, russian, cocktail, classic, vodka, orange). drink(tequila_sunrise, orange, sweet, 15, fruity, mexican, cocktail, classic, tequila, orange). drink(martini, transparent, dry, 40, classic, italian, cocktail, strong, gin, vermouth). drink(long_island_iced_tea, brown, sweet, 22, strong, american, cocktail, classic, vodka, rum). drink(white_russian, white, creamy, 17, sweet, russian, cocktail, classic, vodka, coffee). drink(kamikaze, transparent, sour, 18, sour, japanese, cocktail, strong, vodka, lime). drink(bloody_mary, red, spicy, 12, savory, american, cocktail, classic, vodka, tomato). drink(cosmopolitan, pink, sweet, 18, fruity, american, cocktail, chic, vodka, cranberry). drink(blue_hawaii, blue, fruity, 10, refreshing, hawaiian, cocktail, tropical, rum, blue_curacao). drink(strawberry_daquiri, pink, sweet, 13, fruity, caribbean, cocktail, classic, rum, strawberry). drink(jagerbomb, brown, energetic, 40, powerful, german, shooter, strong, jagermeister, energy_drink). drink(vodka_tonic, transparent, sour, 12, simple, english, cocktail, easy, vodka, tonic). drink(hot_toddy, brown, warming, 20, comforting, scottish, cocktail, warming, whiskey, spices). drink(manhattan, red, dry, 30, classic, american, cocktail, serious, whiskey, vermouth). drink(old_fashioned, brown, strong, 30, classic, american, cocktail, serious, whiskey, bitters). Затем можно создать правила – рекомендации на основе ответов пользователя на вопросы о его вкусовых предпочтениях. Например: % вопросы для определения предпочтений пользователя ask(Color) :- write('Какой цвет напитка Вы хотите? '), nl, write('Варианты ответа: red, yellow, orange, green, white, transparent, brown, pink, blue.'), nl, read(Color). ask(Taste) :- write('Какой вкус Вы предпочитаете? '), nl, write('Варианты ответа: bitter, sour, fruity, minty, sweet, creamy, spicy, dry, energetic, warming.'), nl, read(Taste). ask(Alcohol) :- write('Какое алкогольное содержание Вы предпочитаете? '), nl, write('Варианты ответа: от 8 до 40.'), nl, read(Alcohol). ask(Property) :- write('Какие характеристики напитка Вы предпочитаете? '), nl, write('Варианты ответа: light, refreshing, creamy, easy, sour, sweet, powerful, savory, fruity, classic, tropical, chic, serious, warming, comforting.'), nl, read(Property). ask(Category) :- write('Какую категорию напитка Вы предпочитаете? '), nl, write('Варианты ответа: cocktail, shooter.'), nl, read(Category). ask_ingredient(Ingredient) :- write('Интересует ли Вас наличие какого-то конкретного ингредиента? '), nl, write('Введите "да" или "нет". '), nl, read(IngredientResponse), (IngredientResponse = да -> write('Введите наименование ингредиента: '), read(Ingredient); Ingredient = none). % правило поиска напитка, соответствующего предпочтениям пользователя recommend(Drink) :- ask(Color), ask(Taste), ask(Alcohol), ask(Property), ask(Category), ask_ingredient(Ingredient), (Ingredient = none -> (recommend_color(Color, Drink), recommend_taste(Taste, Drink), recommend_alcohol(Alcohol, Drink), recommend_property(Property, Drink), recommend_category(Category, Drink)); (recommend_ingredient(Ingredient, Drink), recommend_color(Color, Drink), recommend_taste(Taste, Drink), recommend_alcohol(Alcohol, Drink), recommend_property(Property, Drink), recommend_category(Category, Drink))), nl, write('Рекомендуемый напиток: '), write(Drink). Теперь можно запускать программу и получать рекомендации на основе ответов пользователя на вопросы. Например: ?- recommend(Drink). Какой цвет напитка Вы хотите? Варианты ответа: red, yellow, orange, green, white, transparent, brown, pink, blue. |: orange. Какой вкус Вы предпочитаете? Варианты ответа: bitter, sour, fruity, minty, sweet, creamy, spicy, dry, energetic, warming. |: sweet. Какое алкогольное содержание Вы предпочитаете? Варианты ответа: от 8 до 40. |: 15. Какие характеристики напитка Вы предпочитаете? Варианты ответа: light, refreshing, creamy, easy, sour, sweet, powerful, savory, fruity, classic, tropical, chic, serious, warming, comforting. |: fruity. Какую категорию напитка Вы предпочитаете? Варианты ответа: cocktail, shooter. |: cocktail. Интересует ли Вас наличие какого-то конкретного ингредиента? Введите "да" или "нет". |: да. Введите наименование ингредиента: orange. Рекомендуемый напиток: mimosa. В зависимости от потребностей, можно изменять вопросы и добавлять дополнительные характеристики напитков и соответствующие правила рекомендаций.

question:используй dynamic

answer:Использование dynamic позволяет во время выполнения программы добавлять и удалять знания из базы данных, что может быть полезным при создании экспертной системы для рекомендации напитков. Чтобы использовать dynamic, необходимо объявить предикаты, которые будут изменяться, как динамические. Например, для создания и изменения знаний о напитках, можно использовать следующие динамические предикаты: :- dynamic drink/10. drink(negroni, red, bitter, 23, strong, italian, cocktail, classic, gin, herbs). drink(margarita, yellow, sour, 15, refreshing, mexican, cocktail, classic, tequila, citrus). drink(mimosa, orange, fruity, 8, light, french, cocktail, brunch, prosecco, orange). drink(mojito, green, minty, 8, refreshing, cuban, cocktail, classic, rum, mint). drink(pina_colada, white, sweet, 12, creamy, caribbean, cocktail, tropical, rum, pineapple). drink(screwdriver, orange, sour, 11, easy, russian, cocktail, classic, vodka, orange). drink(tequila_sunrise, orange, sweet, 15, fruity, mexican, cocktail, classic, tequila, orange). drink(martini, transparent, dry, 40, classic, italian, cocktail, strong, gin, vermouth). drink(long_island_iced_tea, brown, sweet, 22, strong, american, cocktail, classic, vodka, rum). drink(white_russian, white, creamy, 17, sweet, russian, cocktail, classic, vodka, coffee). drink(kamikaze, transparent, sour, 18, sour, japanese, cocktail, strong, vodka, lime). drink(bloody_mary, red, spicy, 12, savory, american, cocktail, classic, vodka, tomato). drink(cosmopolitan, pink, sweet, 18, fruity, american, cocktail, chic, vodka, cranberry). drink(blue_hawaii, blue, fruity, 10, refreshing, hawaiian, cocktail, tropical, rum, blue_curacao). drink(strawberry_daquiri, pink, sweet, 13, fruity, caribbean, cocktail, classic, rum, strawberry). drink(jagerbomb, brown, energetic, 40, powerful,

question:Sanxan is a novel polysaccharide produced by Sphingomonas sanxa- nigenens NX02 (DSM 19645) (Huang et al., 2009). The tetrasaccharide repeat unit of sanxan has been identified and reported as follows (Huang et al., 2016): →4) β-D-Man (1 → 4) β-D-GlcA (1 → 3) α -L-Rha (1 → 3) β-D-Glc (→1) (Huang et al., 2016). In 2020, sanxan was approved by the China National Center for Food Safety Risk Assessment for use as a food additive. Currently, sanxan is mainly used as a thickener, stabilizer, and coagulant for fruit and vegetable juices (pulps), plant protein drinks, meat enemas, and other food products. When the characteristics and safety of sanxan are recognized (Announcement No.4, 2020 of the Na- tional Health Commission of China), the use of sanxan in the food, medical, and pharmaceutical industries may be gradually popularized.

answer:Sanxan is a novel polysaccharide produced by the bacterium Sphingomonas sanxanigenens NX02. Its tetrasaccharide repeat unit has been identified and approved for use as a food additive in China. Sanxan is mainly used as a thickener, stabilizer, and coagulant in various food products such as fruit and vegetable juices, plant protein drinks, and meat enemas. As its characteristics and safety are recognized, its use may be expanded to other industries such as medical and pharmaceutical.

question:In recent years, some novel biopolymer-secreting strains have been isolated from 73 diverse environments. Sphingomonas sanxanigenens, a member of a new species of the 74 genus Sphingomonas ( Huang et al., 2009 ), synthesizes a biopolymer called sanxan. 75 Sanxan can be precipitated when the pH of fermentation broth was adjusted to 3.0. In 76 contrast to precipitation with alcohol, the cost of extracting sanxan decreases 77 significantly. Sanxan has been used as oil well drilling fluids in China ( Huang et al., 78 2013 ). However, the information on structural characterization of sanxan is lacking. In 79 this work, we investigated chemical structures and physical properties of sanxan 80 polysaccharide from S. sanxanigenens.

answer:The authors of this study isolated Sphingomonas sanxanigenens from a diverse range of environments and found that it produces a biopolymer called sanxan. Sanxan can be easily precipitated from fermentation broth by adjusting the pH to 3.0, which reduces the cost of extraction compared to using alcohol. Sanxan has already been used as oil well drilling fluid in China, but little is known about its structural characterization. Therefore, the authors investigated the chemical structures and physical properties of sanxan polysaccharide from S. sanxanigenens in this study.