In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
How to obtain the truth about knowledge by considering the axiology and anthology aspects of knowledge is the challenge that epistemology must solve. While in scientific epistemology, the accumulation of information that is true will affect how inquiries about the universe are answered heuristically and how natural occurrences are predicted. The primary goal and aim of epistemology, a subfield of philosophy of science, is to investigate and ascertain the nature of knowledge. As such, it examines the origin, sources, and importance of validity from knowledge in addition to discussing the extent and veracity of science. The goal of NLP, a branch of artificial intelligence (AI), is to enable computers to comprehend human language. For instance, text and voice, which people frequently utilize in casual discussions. Integrating computational linguistics with predictive methods led to the development of NLP. NLP has so far done well with text and audio data. There are still others who believe that NLP is in decline, particularly when it comes to managing idioms and sarcasm in contextual data. Due to the vast number of local languages spoken worldwide, the millions of words they contain, the hundreds of regional accents, and their importance in preventing the extinction of local languages, even machine translation, which was the initial purpose of NLP, may still be investigated further. Masalah yang harus dihadapi oleh Epistomologi adalah bagaimana mendapatkan kebenaran akan pengetahuan dengan menimbang aspek antologi dan aksiologi pada pengetahuan. Sedangkan pada epistomologi ilmiah, penyusunan kebenaran suatu pengetahuan akan berpengaruh untuk menjawab pertanyaan di dunia secara heuristis serta dalam memprediksi fenomena alam yang terjadi. Mempelajari dan menentukan hakikat dari suatu pengetahuan adalah fungsi dan tugas utama epistomologi sebagai salah satu cabang dari filsafat ilmu, maka tidak hanya berbicara tentang kebenaran ilmu pengetahuan dan ruang lingkup pengetahuan, akan tetapi secara luas epistomologi juga mempelajari tentang asal mula, sumber dan juga nilai validitas dari pengetahuan. Pemrosesan bahasa alami, atau NLP, adalah bagian dari kecerdasan buatan (AI) yang berkaitan dengan memberi komputer kemampuan untuk memahami bahasa alami manusia. Misalnya teks dan suara yang sering digunakan manusia dalam percakapan sehari-hari. NLP dibuat dengan menggabungkan linguistik komputasi dengan model statistic. Sampai saat ini NLP memiliki performa yang baik pada data teks dan audio. Namun, masih ada orang yang menilai penurunan dunia NLP, terutama dalam penanganan sarkasme dan idiom dalam data kontekstual. Bahkan terjemahan mesin yang merupakan tujuan awal NLP masih dapat dieksplorasi lebih dalam, karena ada banyak bahasa lokal di dunia, ada jutaan kata, ratusan aksen lokal, dan perannya untuk menyelamatkan Bahasa Lokal dari kepunahan.
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