Relevant bibliographies by topics / Algortimi

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Algortimi'

Author: Grafiati
Published: 9 March 2023
Last updated: 19 July 2025

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Journal articles on the topic "Algortimi"

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Zhou, Shi Bo, and Wei Xiang Xu. "Local Outlier Detection Algorithm Based on Coefficient of Variation." Applied Mechanics and Materials 635-637 (September 2014): 1723–28. http://dx.doi.org/10.4028/www.scientific.net/amm.635-637.1723.

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Local outliers detection is an important issue in data mining. By analyzing the limitations of the existing outlier detection algorthms, a local outlier detection algorthm based on coefficient of variation is introduced. This algorthms applies K-means which is strong in outliers searching, divides data set into sections, puts outliers and their nearing clusters into a local neighbourhood, then figures out the local deviation factor of each local neighbourhood by coefficient of variation, as a result, local outliers can more likely be found.The heoretic analysis and experimental results indicate that the method is ef fective and efficient.
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Marwondo, Marwondo, and Taufik Hidayah. "Perbandingan Algoritma Long Short-Term Memory (LSTM) dan Gated Recurrent Unit (GRU) Untuk Prediksi Harga Emas Dunia." In Search 21, no. 2 (2023): 230–39. http://dx.doi.org/10.37278/insearch.v21i2.600.

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Harga emas dunia dapat berubah-ubah secara fluktuatif. Berbagai algoritma prediksi bisa diterapkan untuk mendapatkan akurasi prediksi dengan tepat, termasuk algoritma Long Short-Term Memory (LSTM), dan Gated Recurrent Unit (GRU). Di antara kedua algortitma tersebut, manakah algortima yang memiliki performa terbaik dalam memprediksi haga emas dunia? Dataset yang digunaan berasal dari dari website The London Bullion Market Association (LBMA) yang berbentuk time series dari tahun 1968 sampai 2022. Parameter yang digunakan untuk perbandingan yaitu Mean Squared Error (MSE), Root Mean Squared Error (RMSE), dan Mean Absolute Error (MAE). Setelah dilakukan proses Training dan Evaluasi dengan menguji data test dihasilkan sebuah analisa bahwa algoritma GRU memberikan performa yang lebih baik dibandingkan dengan LSTM karena memiliki nilai loss/error lebih rendah dalam memprediksi harga emas dunia.
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Nuryaman, Yosep, Bibit Sudarsono, Ummi Faddillah, and Ayuni Asistyasari. "Klasifikasi Data Penjualan Mengunakan Algoritma K-Means Dan Analytic Hierarchy Process." Jurnal Larik: Ladang Artikel Ilmu Komputer 2, no. 1 (2022): 23–28. http://dx.doi.org/10.31294/larik.v2i1.1371.

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Dengan adanya Covid 19 yang telah melanda beberapa tahun terakhir ini membuat penjualan di berbagai bidang mengalami dampak negatif tak terkecuali bagi Swalayan X yang mengalami penurunan di berbagai cabang yang terbagai ke beberapa daerah. Sebagai bahan pertimbangan, mereka melakukan evaluasi terhadap penjualan cabang-cabang tersebut. Dengan mengklasifikasikan data penjualan yang ada diharapkan mereka mampu melihat mana kelompok cabang swalayan x yang kurang baik mana yang sudah baik. Namun perlu adanya teknik klasifikasi yang baik agar evaluasi yang dilakukan bedasarkan hasil perhitungan yang baik. Oleh sebab itu penulis mencoba menggunakan Algoritma K-Mean dan Algortima AHP untuk mengklasifikan data penjualan yang ada. Algoritma K-Mean dan Algortma AHP merupakan algoritma yang mampu mengklusterisasi sekumpulan data. Dengan mengklusteriasi toko-toko berdasarkan kedekatan hasil penjualan selama 2 tahun terakhir yang naik turun dengan menggunakan 2 algoritma tersebut nantinya akan mampu melihat toko mana tergolong baik dan mana yang tergolong kurang baik. Berdasarkan hasil perbandingan dari hasil perhitungan, didapakan bahwa hasil terbaik yaitu menggunakan algoritma K-Mean dengan k2 pada literasi ke 3 dengan rasio 0,04926
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DePano, N. Adlai A., Farinaz D. Boudreaux, Philip Katner, and Brian Li. "Algorthmic pradigms." ACM SIGCSE Bulletin 22, no. 1 (1990): 186–91. http://dx.doi.org/10.1145/319059.323448.

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Sudewo, Raden Tio Putra, Yovi Pratama, and Elvi Yanti. "Analisis Data Mining Untuk Prediksi Kanker Payudara Menggunakan Algoritma Klasifikasi." Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) 3, no. 2 (2023): 62–69. http://dx.doi.org/10.55382/jurnalpustakadata.v3i2.656.

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Kanker payudara merupakan salah-satu kanker yang menyerang jaringan pada payudara yang mana lebih sering dialami oleh perempuan tetapi tidak menutup kemungkinan juga menyerang laki-laki (sangat jarang terjadi). Penerapan data mining dalam meneliti pasien kanker payudara adalah untuk menjadikan sebuah landasan dalam mengetahui akurasi dari model yang di bangun guna menentukan penderita kanker payudara dengan penggolongan “ganas” atau “jinak” dengan menggunakan naïve bayes dan C4.5. Pengujian dilakukan dengan beberapa eksperimen yaitu perhitungan split data 60%, 70%, dan 80 %. Pengujian data mengenai kanker payudara memiliki akurasi yang tinggi pada split data 70 % menggunakan algortima c4.5 dan memiliki accuracy yang lebih tinggi yaitu 99.4975 % dibandingkan dengan mode pengujian lainnya, sedangkan accuracy terendah adalah split data 80 % pada algortima naïve bayes yaitu 95.1648%. Pada perhitungan yang membandingkan algoritma C4.5 dan algoritma naïve bayes, dapat dikatakan bahwa algortima C4.5 sebagai algoritma yang efektif baik dari perhitungan ataupun hasil akhir yang mana pengujian tersebut dapat dijadikan suatu landasan terkait kanker payudara mengingat hasil akurasi dari algortima C4.5 menyentuh 99.4975 % sedangkan hasil dari algortima naïve bayes hanya menyentuh 95.8944 %.
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Sodikin, Luthfia, Tineke Fatma Putri, and Taufik Hidayat. "Analisa Kompresi File Teks Menggunakan Algortima Huffman." Journal ICTEE 3, no. 1 (2022): 10. http://dx.doi.org/10.33365/jictee.v3i1.1271.

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Era Digital saat ini memiliki dampak besar bagi kelestarian alam, selain mengurangi penggunaan kertas dengan adanya berkas berbentuk file membuat arsip yang tersimpan lebih tertata rapih dengan kurun waktu yang lama. Di masa pandemi pemanfaatan digital menjadi peran penting dalam kelangsungan kehidupan yang mengharuskan kegiatan tanpa harus kontak langsung. Dengan begitu banyak pekerjaan pekerjaan yang diselesaikan dirumah kemudian dibantu dengan Internet untuk melakukan proses kirim/terima file. File merupakan data yang sudah diolah menjadi sebuah informasi berupa teks, video, gambar, dan suara. Dalam proses pengiriman tidak jarang terjadinya kendala yakni ukuran file terlalu besar karena media penyimpanan yang digunakan hanya sedikit. Kompresi data adalah ilmu yang menampilkan informasi dalam bentuk yang pendek tujuannya untuk mengurangi jumlah bit yang digunakan untuk menyimpan atau mengirim informasi. Sedangkan Algoritma Huffman adalah teknik kompresi yang tidak mengubah informasi data dari aslinya. Prinsip kode Huffman yaitu karakter yang paling sering muncul di dalam data dikodekan dengan kode yang jumlah bitnya lebih sedikit, sedangkan karakter yang jarang muncul dikodekan dengan kode yang jumlah bitnya lebih panjang. Kompresi file dibutuhkan untuk mempercepat proses pengiriman data antar jaringan komputer. Perkembangan teknologi saat ini menyebabkan kebutuhan data serta perpindahan data dari satu perangkat ke perangkat lain meningkat. Data-data tersebut umumnya dikompresi terlebih dahulu agar proses pertukaran tidak memakan waktu yang lama. Dengan menggunakan algoritma huffman Rasio Kompresi yang dihasilkan untuk file audio dan image rasio kompresi yang dihasilkan lebih kecil sedangan untuk file teks rasio kompresi yang dihasilkan lebih besar. Tingkat keamanan data setelah dikompresi tidak berkurang atau mengalami kerusakan setelah proses kompresi data dilakukan Kecepatan proses kompresi dan dekompresi data setara dengan ukuran dan jenis file. File hasil dekompresi akan berhasil seperti file semula sebelum dikompresi, kecepatan proses kompresi dan dekompresi data setara dengan ukuran dan jenis file dan Kompresi file juga kurang berhasil jika isi file terlalu sedikit sehingga ukuran file asli bisa jadi lebih kecil dari file hasil kompresi karena file kompresi masih harus menyimpan huffman tree-nya.
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Gupta, Sandeep, and A. K. Sharma. "STATCOM �Its Control Algorthim." i-manager's Journal on Electrical Engineering 3, no. 4 (2010): 41–45. http://dx.doi.org/10.26634/jee.3.4.1189.

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Irfan, Miftahul, Wardhani Utami Dewi, Khoirin Nisa, and Mustofa Usman. "IMPELEMENTASI K-NEAREST NEIGHBORS, DECISION TREE DAN SUPPORT VECTOR MECHINE PADA DATA DIABETES." Jurnal Mahasiswa Ilmu Komputer 4, no. 2 (2023): 137–50. http://dx.doi.org/10.24127/ilmukomputer.v4i2.4007.

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Diabetes merupakan salah satu penyakit yang menjadi penyebab kematian terbesar didunia. Kasus kematiannya pun tercatat lebih dari 4 juta pada tahun 2019. Diabetes juga dapat menyebabkan timbulnya penyakit lainnya. Bahaya diabetes ini menjadi perhatian khusus WHO. Seiring dengan perkembangan teknologi ini, banyak sekali kolaborasi antara bidang kesehatan, statistic dan computer untuk menanggulangi berbagai macam penyakit. Algortima machine learning menjadi popular dalam proses klasifikasi data dan sudah banyak diterapkan pada data kesehatan. Dengan begitu pada artikel ini akan dilakukan perbandingan algoritma machine learning KNN, Decision Tree, dan SVM untuk melihat algortima mana yang paling cocok untuk klasifikasi data diabetes. Hasil menunjukkan bahwa KNN dan SVM memiliki akurasi yang cukup besar yaitu 81,13%. Sehingga kedua algortima tersebut dapat menjadi rekomendasi proses klasifikasi data diabetes sehingga dapat membantu dokter dalam menanggulangi penyakit diabetes. Hasil ini juga menunjukkan bahwa 8 variabel yang digunakan berpengaruh terhadap resiko diabetes
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Sembiring, Misdem, and Fauzi Haris Simbolon. "Perancangan Perangkat Lunak Pembelajaran Algoritma Hamming Code dalam Mencari Bit Error pada Komunikasi Data." LOFIAN: Jurnal Teknologi Informasi dan Komunikasi 1, no. 1 (2021): 24–28. http://dx.doi.org/10.58918/lofian.v1i1.161.

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Dalam ilmu komputer terdapat bermacam-macam algoritma dalam mendeteksi serta mengoreksi error ketika transmisi data digital berlangsung. Salah satu algoritma untuk mendeteksi error adalah dengan menggunanakan Hamming Code dengan single error corrention. Metode ini sangat cocok digunakan pada situasi dimana terdapat beberapa error yang teracak (randomly occurring errors). Metode Hamming Code menyisipkan (n + 1) check bit ke dalam 2n data bit. Metode ini menggunakan operasi XOR (Exclusive - OR) dalam proses pendeteksian error, dengan nilai Input dan output data berupa bilangan biner. Peneliti bermaksud untuk merancang perangkat lunak pembelajaran yang mampu menjelaskan teknik pendeteksian error dari algoritma Hamming Code. Panjang data input dan output pada algortima Hamming Code minimal harus sama dengan 4 bit. Atau dengan perkataan lain, algortima Hamming Code tidak mendukung data dengan panjang 2 bit. Algortima Hamming Code tidak mampu melakukan pengecekan terhadap posisi data error (bad bit) yang lebih dari satu buah.
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Sianturi, Fricles Ariwisanto, Mina Kumari, and Erlina Laian. "Implementasi Algortima C4.5 Menentukan Pola Berangkatan Jamaah Haji." Jurnal Sains dan Teknologi 3, no. 2 (2022): 66–70. http://dx.doi.org/10.55338/saintek.v3i2.260.

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Determination of the Hajj Pilgrim Departure Pattern is currently very much needed by the Haj organizers, especially at the Office of the Ministry of Religion Lubuk Pakam because the schedule of pilgrims' departure is still not regular, causing accumulation of data on pilgrims who will be departed to the holy land, but with The number of pilgrims who will depart for the pilgrimage is made to determine the pattern of Hajj departure with the C4.5 Algorithm to make it easier for the hajj organizer staff to determine what age should be sent to the holy land.
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Dissertations / Theses on the topic "Algortimi"

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Scandellari, Carolina. "Algortimi di spike detection per applicazioni neuroprotesiche: sviluppo di modelli, implementazione e valutazione delle performance." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/19904/.

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I disordini neurologici costituiscono il 6,3% delle cause di malattia in tutto il mondo, diventando una delle priorità della sanità globale. Per trattare questi disordini si utilizzano farmaci, ma alcuni pazienti possono risultarne resistenti. La Neuroingegneria propone soluzioni innovative per la cura e la riabilitazione di queste patologie, proponendo, tra le varie soluzioni, le neuroprotesi, capaci di sostituire un’area danneggiata del cervello o di ricollegare artificialmente due aree disconnesse bypassando la lesione che ha causato il danno. Tra questi, il dispositivo sviluppato presso la University of Kansas (KUMC) si è dimostrato essere efficace in esperimenti effettuati su topi con lesione focale in area motoria. Il funzionamento di questo dispositivo è basato sull’impianto di micro-elettrodi in due regioni cerebrali disconnesse a causa di una lesione. Questi creano un ponte in grado di ricollegare le due aree scollegate attraverso la registrazione di eventi (spike) in una delle due aree, e la seguente somministrazione di corrente nella seconda. In questo tipo di dispositivi, è importantissimo effettuare una identificazione corretta degli spikes. Il mio lavoro di tesi si inserisce nell’ambito della collaborazione tra il Rehab Technologies Lab (IIT, Genova), dove ho svolto il tirocinio, e la KUMC in relazione al progetto per lo sviluppo di neuroprotesi innovative per il recupero motorio a seguito di danni cerebrali. Nello specifico, il mio lavoro di Tesi si concentra sulla Spike Detection (SD), di cui uno dei problemi fondamentali è la mancanza di un ground truth, ovvero di una conoscenza a priori della localizzazione degli spikes nel tracciato. Nel contesto descritto sopra, si inseriscono gli obiettivi di questa Tesi: fornire un ground truth, studiare e adattare un set di algoritmi di SD già presenti in letteratura, modificare un algoritmo ad alte prestazioni sviluppato all’interno di IIT in passato e confrontare le prestazioni di tutti gli algoritmi di SD.
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CICCOLELLA, SIMONE. "Practical algorithms for Computational Phylogenetics." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/364980.

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In questo manoscritto vengono discussi le principali sfide computazionali nel campo della inferenza di filogenesi tumorale a vengono proposte diverse soluzione per i tre principali problemi di (i) ricostruzione dell'evoluzioni di un campione tumorale, (ii) clustering di dati SCS per una piu' pulita e veloce inferenza e (iii) il confronto di diverse filogenesi. Inoltre viene discusso come combinare le diverse soluzioni in una singola pipeline per una piu' rapida analisi.<br>In this manuscript we described the main computational challenges of the cancer phylogenetic field and we proposed different solutions for the three main problems of (i) the progression reconstruction of a tumor sample, (ii) the clustering of SCS data to allow for a cleaner and faster inference and (iii) the evaluation of different phylogenies. Furthermore we combined them into a usable pipeline to allow for a faster analysis.
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Šarda, Petr. "Algortimy pro sestavování puzzle." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219709.

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This diploma thesis deals with constructing of algorithms of consisting a puzzle and suggesting of the workplace for its imaging. There are studied two methods of forming a puzlle. First method is forming of the puzzle with a known pattern. For this method is used the Harris operator and the correlation. In the second method is the puzzle formed without a pattern. Fot this method is used the correlation. In the last part there is a mutual evaluation of these two methods.
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Muller, Andreas. "Message passing algorthms in wireless communications." Thesis, University of Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544340.

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Tabatabaian, Seyed Jalil. "Cryptanalysis algortihms for public key cryptosystems." Thesis, University of Newcastle Upon Tyne, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283904.

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Bangert, Patrick David. "Algorthmic problems in the braid groups." Thesis, University College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417929.

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Yuret, Deniz. "From genetic algorthms to efficient optimization." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/37727.

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Vahl, Christopher Irvin. "Algortihms for constructing D-optimal designs for multilevel experiments /." Search for this dissertation online, 2005. http://wwwlib.umi.com/cr/ksu/main.

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Newman, Aaron R. (Aaron Roy). "An improved scheduling algorthim for space-based surveillance sensors." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/49588.

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Yeung, Chun. "A PERFORMANCE COMPARISON OF CLUSTERING ALGORITHMS IN AD HOCNETWORKS." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2393.

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An ad hoc network is comprised of wireless mobile nodes without the need of wired network infrastructure. Due to the limited transmission range of nodes, the exchange of data between them may not be possible using direct communication. Partitioning the network into clusters and electing a clusterhead for each cluster to assist with the resource allocation and data packet transmissions among its members and neighboring clusterheads is one of the most common ways of providing support for the existing ad hoc routing protocols. This thesis presents the performance comparison of four ad hoc network clustering protocols: Dynamic Mobile Adaptive Clustering (DMAC), Highest-Degree and Lowest-ID algorithms, and Weighted Clustering Algorithm (WCA). Yet Another Extensible Simulation (YAES) was used as the simulator to carry out the simulations.<br>M.S.Cp.E.<br>School of Electrical Engineering and Computer Science<br>Engineering and Computer Science<br>Computer Engineering
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Books on the topic "Algortimi"

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United States. National Aeronautics and Space Administration., ed. Final report to the National Aeronautics and Space Agency for Power spectral estimation algorthms [i.e. algorithms]: (contract no. NAG-5-499). Bowie State University, 1990.

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Stross, Charles. Antibodies. AudioText, 2005.

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millonarioemprendedor, Daniel Martinez. Guia Completa para Instagram Marketing: 5 Pasos para Crear Tu Perfil de Instagram y Consejos para Romper el Algortimo. Independently Published, 2020.

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Goodrich. Website to Accompany Data Structures & Algortihms in Java 3e (Http://datastructures.net) Solns, Slides, Add'l Problems, Applets + More. John Wiley & Sons Inc, 2004.

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Book chapters on the topic "Algortimi"

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Özçelik, Ahmet Devlet, and Ahmet Sinan Öktem. "Damage Detection on Turbomachinery with Machine Learning Algortihms." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-50920-9_19.

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Hanumanthu, M., Shaik Karimullah, M. Sravani, et al. "Facemask Detection Using Bounding Box Algortihm Under COVID-19 Circumstances." In Studies in Computational Intelligence. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-43009-1_9.

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Gabr, B., and M. Ahmed. "Assessment of Genetic Algorthim in Developing Bathymetry Using Multispectral Landsat Images." In APAC 2019. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0291-0_55.

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Popa, C. L., L. F. Parpala, and T. Aurite. "Problem Solving Algortihm for the Manufactruring Department Using Agent Technology." In DAAAM International Scientific Book 2008. DAAAM International, 2008. http://dx.doi.org/10.2507/daaam.scibook.2008.51.

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Revathi, T., and K. Muneeswaran. "Congestion Control Using Soft Computing." In Soft Computing Applications for Database Technologies. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-814-7.ch014.

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In the recent Internet era the queue management in the routers plays a vital role in the provision of Quality of Service (QoS). Virtual queue-based marking schemes have been recently proposed for Active Queue Management (AQM) in Internet routers. In this chapter, the authors propose Fuzzy enabled AQM (F-AQM) scheme where the linguistics variables are used to specify the behavior of the queues in the routers. The status of the queue is continuously monitored and decisions are made adaptively to drop or mark the packets as is done in Random Early Discard (RED) and Random Early Marking (REM) algorthms or schemes. The authors design a fuzzy rule base represented in the form of matrix indexed by queue length and rate of change of queue. The performance of the proposed F-AQM scheme is compared with several well-known AQM schemes such as RED, REM and Adaptive Virtual Queue (AVQ).
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Engelmann, Alana Gabriela. "O USO DOS ALGORTIMOS COMO MEIO DE FORMAÇÃO DA DECISÃO JUDICIAL E O ACCOUNTABILITY." In TEORIA CRÍTICA DO PROCESSO - Segunda Série. RFB Editora, 2022. http://dx.doi.org/10.46898/rfb.9786558893172.2.

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Wu Chien-Yu, Ho Hann-Jang, and Lee Sing-Ling. "Optimization of Downlink Bandwidth Allocation for Energy Efficiency over OFDMA Wireless Networks." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-484-8-345.

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For the multicast channel assignment issue with multi-layer, this paper studies a resource allocation problem for minimizing the energy consumption of subscriber stations in Orthogonal Frequency Division Multiplexing Access (OFDMA) wireless systems. Not only does the requirement have to be guaranteed when multicast users receive video content in layer-based video coding, but also the energy consumption needs to be minimized. In this paper, the energy consumption of each station is optimized by minimizing the number of active symbols. The scheduling process is divided into two phases. First, the number of requested tiles is minimized by proposed scheme Layer Determination Scheme with SVC (LDS) for the issue of optimizing energy consumption. The proposed LDS scheme determines the modulation of the selected layer and assigns available tiles to the selected layer. In the secondary phase, the symbol scheduling problem is minimizing the number of active symbols for each station. The Complementary Matching Algorithm (CMA) is proposed to minimize the total number of active symbols in an OFDMA wireless system. The problems of symbol scheduling are reduced to the subset sum optimization problem to find the complementary subset of a request. In the simulation results for the proposed LDS and CMA algorithms, we found that the solutions generated by our algortihms have better performance in terms of energy consumption and throughput.
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Conference papers on the topic "Algortimi"

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Shanmugapriya, G., M. Arjun, G. Bhargavaa, and Aswin Sidhaarth. "Blood Pressure Prediction using Machine Learning Algortihms." In 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2024. http://dx.doi.org/10.1109/icacite60783.2024.10616781.

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Badhan, Akash, and Simarjit Singh Malhi. "Enhancing Data Security and Efficiency: A Hybrid Cryptography Approach (AES + ECC) Integrated with Steganography and Compression Algortihm." In 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT). IEEE, 2025. https://doi.org/10.1109/idciot64235.2025.10914830.

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DePano, N. Adlai A., Farinaz D. Boudreaux, Philip Katner, and Brian Li. "Algorthmic pradigms." In the twenty-first SIGCSE technical symposium. ACM Press, 1990. http://dx.doi.org/10.1145/323410.323448.

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Valiant, Leslie G. "Accidental Algorthims." In 2006 47th Annual IEEE Conference on Foundations of Computer Science. IEEE, 2006. http://dx.doi.org/10.1109/focs.2006.7.

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Shea, Peter J., John Peterson, Kathleen Alexander, and Alcino Azevedo. "Force aggregation using genetic algortihms." In Optical Science and Technology, SPIE's 48th Annual Meeting, edited by Oliver E. Drummond. SPIE, 2003. http://dx.doi.org/10.1117/12.506449.

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Braginsky, David, and Deborah Estrin. "Rumor routing algorthim for sensor networks." In the 1st ACM international workshop. ACM Press, 2002. http://dx.doi.org/10.1145/570738.570742.

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Li, Huan, and Chengsheng Pan. "An Adaptive Iterative Algorthm for System Identification." In 2010 3rd International Conference on Intelligent Networks and Intelligent Systems (ICINIS). IEEE, 2010. http://dx.doi.org/10.1109/icinis.2010.27.

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Penaloza Enriquez, Jorge Alberto, Mario I. Chacon-Murguia, Roberto Hernandez-Ceron, and Gerardo Hernandez-Flores. "Algortihm for Daphnia Motion Detection in Toxicological Studies." In 2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). IEEE, 2018. http://dx.doi.org/10.1109/iceee.2018.8533966.

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9

Ruochen Liu, Xiao Wang, Yangyang Li, and Xiangrong Zhang. "Multi-objective Invasive Weed Optimization algortihm for clustering." In 2012 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2012. http://dx.doi.org/10.1109/cec.2012.6256540.

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Tangfei Tao, Ja Choon Koo, and Hyouk Ryeol Choi. "A fast block matching algorthim for stereo correspondence." In 2008 IEEE Conference on Cybernetics and Intelligent Systems (CIS). IEEE, 2008. http://dx.doi.org/10.1109/iccis.2008.4670774.

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