Practice question on GA

Duration: 5 min

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Inside: a video lesson and guided study material.

Module outline

  1. About Course: UPPSC Course Overview
  2. Interview Preparation & Guidance: Interview Preparation
  3. Paper 1 | General Hindi: भाषा, लिपि, ध्वनि, वर्ण, अक्षर, स्वर, व्यंजन, मात्रा और संयुक्ताक्षर, वर्तनी, वर्ण-विन्यास, अनुस्वार, अनुनासिक, चंद्रबिंदु और ‘र’ के रूप, शब्द, पद और शब्द-भेद, संज्ञा और सर्वनाम, विशेषण और क्रिया, लिंग, वचन, पुरुष और कारक, काल, वाच्य, वाक्य और वाक्य-भेद, वर्णमाला, समास, संधि, विलोम शब्द, पर्यायवाची शब्द, सामान्य अशुद्धियाँ, अनेक शब्दों के लिए एक शब्द, मुहावरे और लोकोक्तियाँ, अपठित गद्यांश और अपठित पद्यांश, Multi-Topic Content (Cross-Concept Material), शब्द-भंडार, वर्ण-विचार, हिन्दी की ध्वनि और स्वनिम व्यवस्था, प्राचीन और मध्यकालीन भारतीय आर्यभाषाएँ, काव्य के लक्षण, हेतु और प्रयोजन, अशुद्धि-शोधन, शब्द-रचना, शब्द-भेद, हिन्दी की रूप रचना, रूप-रचना, हिन्दी शब्द रचना, हिन्दी साहित्येतिहास दर्शन, भक्तिकालीन काव्यधाराएँ, भारतीय काव्यशास्त्र की परंपरा, भारतीय नवजागरण और स्वाधीनता आंदोलन, अन्य गद्य विधाएँ एवं प्रवासी साहित्य, निर्धारित उपन्यासों का तुलनात्मक अध्ययन, गोदान, हिन्दी कहानी का विकास, स्वातंत्र्योत्तर और नयी कहानी, हिन्दी निबंध का विकास, शुक्लोत्तर निबंध, द्विवेदी और शुक्ल युग के निबंध, हिन्दी की संवैधानिक स्थिति, आधुनिक भारतीय आर्यभाषाएँ और हिन्दी का उद्भव, हिन्दी भाषा प्रयोग के विविध रूप, रीतिकाल, जीवनी, द्विवेदी युग और छायावाद, रीति, वक्रोक्ति और औचित्य सिद्धान्त, शब्दशक्ति और ध्वनि सिद्धान्त, रस सिद्धान्त और साधारणीकरण, उत्तर आधुनिकतावाद, लोहिया दर्शन, हिन्दी उपन्यास का विकास, हिन्दी नवजागरण, अंबेडकर दर्शन, आदिकाल, प्रयोगवाद और नयी कविता, छायावादी काव्य: प्रसाद और निराला, प्रगतिवाद से समकालीन कविता, निर्गुण भक्ति काव्य, द्विवेदीयुगीन काव्य, रीतिकालीन काव्य, आरंभिक हिन्दी उपन्यास, स्वातंत्र्योत्तर उपन्यास, आत्मकथा, स्वाधीनता-पूर्व प्रेमचंदोत्तर उपन्यास, निर्धारित कहानियों का तुलनात्मक अध्ययन, साठोत्तरी नाटक, प्रसाद और प्रसादोत्तर युग के नाटक, भारतेन्दु युगीन नाटक, स्वातंत्र्योत्तर नाटक, भारतेन्दु युगीन निबंध, संस्मरण और रेखाचित्र, व्यंग्य, एक साहित्यिक की डायरी, संस्कृति के चार अध्याय, सगुण भक्ति काव्य, हिन्दी नाटक, एकांकी और रंगमंच, आधुनिक गद्य और हिन्दी नवजागरण, अलंकार सिद्धान्त, हिन्दी आलोचना का विकास, भक्ति आंदोलन, कल्पना, बिम्ब, प्रतीक, मिथक और फंतासी, नयी कविता का विस्तार और साठोत्तरी कविता, उत्तर-छायावादी और प्रगतिवादी काव्य, काव्यगुण और काव्यदोष, प्लेटो, अरस्तू और पाश्चात्य परंपरा, मार्क्सवाद, स्वच्छन्दतावादी काव्यशास्त्र, आधुनिक पाश्चात्य आलोचना, भाषा और भाषा परिवार, देवनागरी लिपि
  4. Paper 2 | General Studies: State Wise GK, Polity, Geography, History, GK- Current Affairs
  5. Paper 1 | Programming Language: Language Design, C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling, OOPS with C++
  6. Paper 1 | Database Management Systems: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Relational Calculus, Transaction Management, Concurrency Control, ORDBMS, NoSQL
  7. Paper 1 | Cyber Security: Society, Law & Ethics, Cyber Threats and Malware Attacks, Role of Internet and Web Services, Security in Mobile and Wireless Computing, Electronic Data Interchange and E-Commerce, Physical Security and Cryptography Basics, Intrusion Detection Systems (IDS), Cyber Safety and Security, Ethical Hacking
  8. Paper 1 | Computer Organization and Architecture: Basics of COA, Programming the Basic Computer, Cache Memory Organization, Input Output Organisation, Instr Formats & Modes, Register Transfer and Microoperations, Control Unit Design
  9. Paper 1 | Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security
  10. Paper 1 | Design and Analysis of Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  11. Paper 1 | Data Structures: Introduction to DS, Array, Linked List, Stack, Queue, Tree, Graphs, Hashing
  12. Paper 1 | Discrete Structures and Theory of Logic: Permutation and Combination, Set Theory, Relations, Functions, Propositional and Predicate Logic, Graph Theory, Group Theory
  13. Paper 1 | Software Project Management: Software Project Management
  14. Paper 2 | Operating Systems: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management, Unix OS, Linux OS, Security
  15. Paper 2 | Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment, Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Pushdown Automata & CFG, Complexity Theory
  16. Paper 2 | Artificial Intelligence & High Performance Computing: Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Planning, Multi Agent Systems, Natural Language Processing, Emerging Tech Trends
  17. Paper 2 | Image Processing: Digital Image Fundamentals, Image Enhancement, Image Restoration, Color Image Processing, Image Compression
  18. Paper 2 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  19. Paper 2 | Computer Graphics: Basics of Computer Graphics, 2-D Geometrical Transforms and Viewing, 3-D Object Representation, Geometric Transformations and Viewing
  20. Paper 2 | Web Technologies: Website, Browser & Services, Internet Fundamentals, Web Design & Development, Protocols & Services, Web Publishing & Hosting, Server Side & Security, Emerging Technologies, HTML Basics, JavaScript-Basics, Java
  21. Paper 2 | Soft Computing: Fuzzy Sets, Artificial Neural Networks, Genetic Algorithms
  22. Paper 2 | Distributed System: Distributed Systems
  23. UPPSC Live Class Recordings: UPPSC Polytechnic Lecturer 2025 (CS)
  24. Previous Year Papers:
  25. Mock Test:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a practice question from the UGC NET Paper-2019 on genetic algorithms, focusing on calculating fitness strength using the formula Sf(x) = f(x)/Σf(x), where f(x) = x². The problem involves determining the fitness strength of the binary chromosome (11000), which is converted to decimal as 24, yielding f(24) = 576. The total sum of fitness values for the population P={(01101), (11000), (01000), (10011)} is computed as 1170.2, resulting in Sf(24) ≈ 0.492 or 49.2%, matching option (d). The instructor demonstrates the calculation step-by-step, writing the formula and intermediate values on a board. Later, the video transitions to explaining selection operators in genetic algorithms, introducing Roulette Wheel Selection with the formula pi = fi / Σfi, where individual fitness (fi) is divided by total population fitness to determine selection probability. A table and pie chart illustrate this with example values: individuals with fitness 15, 20, and 30 have selection probabilities of approximately 24%, 31%, and 45% respectively. The lesson also introduces Elitism Selection as a method to preserve high-performing individuals across generations, emphasizing the role of selection in passing genes to offspring.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video presents a UGC NET Paper-2019 question on genetic algorithms, asking to compute the fitness strength of a binary chromosome (11000) using the formula Sf(x) = f(x)/Σf(x), where f(x) = x². The instructor converts the binary chromosome to decimal (24), calculates f(x) as 576, and computes the sum of all fitness values in the population (Σf(x) = 1170). The normalized fitness strength is then calculated as 576/1170 ≈ 49.2, which is identified as the correct answer (d). The solution includes a step-by-step table showing binary-to-decimal conversion, f(x) = x² computation for each chromosome, and summation of fitness values. The instructor writes the formula and steps on screen, emphasizing the calculation process and highlighting option (d) as correct.

  2. 2:00 – 5:00 02:00-05:00

    The video segment explains the calculation of fitness strength in genetic algorithms using a UGC NET practice question. It begins by presenting chromosome (11000) and demonstrates converting binary values to decimal, applying f(x)=x², summing all fitness values (Σf(x) = 1170), and computing normalized fitness Sf(x) = f(x)/Σf(x). For (11000), this yields 576/1170 ≈ 49.2, identified as the correct answer 'd'. The lesson then transitions to selection operators, introducing Roulette Wheel Selection and Elitism Selection. It defines the selection phase as choosing fittest individuals for reproduction, with Roulette Wheel using fitness proportionality—where probability pi = fi / Σfi determines selection likelihood. A table and pie chart illustrate this, showing how higher fitness values increase the chance of being selected in reproduction.

  3. 5:00 – 5:27 05:00-05:27

    In this segment, the instructor explains the roulette wheel selection method used in genetic algorithms, where individuals are selected based on their fitness values. A table displays individual fitness values and their corresponding probabilities, calculated using the formula pi = fi / Σfi. The probability of selecting an individual is proportional to its fitness, with higher values increasing selection likelihood. A pie chart visually represents the probability distribution across individuals, showing how each contributes to the overall selection chance. The example includes numerical values and percentages, illustrating that an individual with a fitness of 15 has a 100% selection probability when normalized against the total fitness sum. This method ensures that fitter individuals are more likely to be chosen for reproduction in the algorithm.

This lesson segment addresses a UGC NET 2019 practice question on genetic algorithms, focusing on fitness strength calculation and selection operators. The core concept is the computation of normalized fitness using Sf(x) = f(x)/Σf(x), where f(x) = x², applied to a binary chromosome (11000). The instructor demonstrates converting the binary value 11000 to decimal (24), computing f(24) = 576, and summing the fitness values of all chromosomes in the population to obtain Σf(x) = 1170.2, resulting in Sf(24) ≈ 49.2%, which matches option (d). The lesson then transitions to selection mechanisms, introducing Roulette Wheel Selection with the formula pi = fi / Σfi, where individual fitness (fi) is divided by total population fitness to determine selection probability. A table and pie chart illustrate this with example values: individuals with fitness 15, 20, and 30 have selection probabilities of approximately 24%, 31%, and 45% respectively. Elitism Selection is also introduced as a method to preserve high-performing individuals across generations, emphasizing the role of selection in passing genes to offspring. The teaching progression moves from concrete calculation (fitness strength) to abstract concepts (selection operators), enabling students to understand both the numerical computation and its biological analogy in genetic algorithms.

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