Journal articles: 'AMP ALGORITHM'

1

Kparib, Douglas Yenwon, John Awuah Addor, and Anthony Joe Turkson. "A Comprehensive Comparison of Label Setting Algorithm and Dynamic Programming Algorithm in Solving Shortest Path Problems." Journal of Mathematics Research 13, no. 5 (September 21, 2021): 14. http://dx.doi.org/10.5539/jmr.v13n5p14.

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In this paper, Label Setting Algorithm and Dynamic Programming Algorithm had been critically examined in determining the shortest path from one source to a destination. Shortest path problems are for finding a path with minimum cost from one or more origin (s) to one or more destination(s) through a connected network. A network of ten (10) cities (nodes) was employed as a numerical example to compare the performance of the two algorithms. Both algorithms arrived at the optimal distance of 11 km, which corresponds to the paths 1→4→5→8→10 ,1→3→5→8→10 , 1→2→6→9→10  and  1→4→6→9→10 . Thus, the problem has multiple shortest paths. The computational results evince the outperformance of Dynamic Programming Algorithm, in terms of time efficiency, over the Label Setting Algorithm. Therefore, to save time, it is recommended to apply Dynamic Programming Algorithm to shortest paths and other applicable problems over the Label-Setting Algorithm.

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Dahiya, Tripti, Nakul Vashishth, Deepika Garg, Avinash K. Shrivastava, and P. K. Kapur. "Novel Heuristic Algorithm & its Application for Reliability Optimization." International Journal of Mathematical, Engineering and Management Sciences 8, no. 4 (August 1, 2023): 755–68. http://dx.doi.org/10.33889/ijmems.2023.8.4.043.

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Heuristic algorithms are practical, easy to implement, and work fast to provide short-term, feasible solutions for any kind of problem within economical budgets as compared to other meta-heuristic algorithms. This paper presents a novel heuristic algorithm named the Dahiya-Garg Heuristic Algorithm (DG-Alg) to find the optimal solution for constrained reliability redundancy allocation optimization problems. The cornerstone of the novel DG-Alg is its novel selection factor, which is a mathematical formula that helps the heuristic algorithm search for optimal subsystems for reliability optimization. A novel formulated selection factor in DG-Alg has increased its effectiveness and efficiency. To analyze the performance of the proposed heuristic algorithm and the other three existing heuristic algorithms, they are applied to a problem taken from a pharmaceutical manufacturing plant named Yaris Pharmaceuticals. During the application of the heuristic algorithms, it was ensured that redundancy allocation was done within stipulated cost constraints. Further, a comparative analysis of the obtained results has been done to judge the performance of the proposed heuristic algorithm. It is deduced that the proposed heuristic algorithm gives optimized and computationally efficient results in comparison to the other existing heuristic algorithms.

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Kanagasabai, Lenin. "Two bio-inspired algorithms for solving optimal reactive power problem." International Journal of Advances in Applied Sciences 9, no. 3 (September 1, 2020): 180. http://dx.doi.org/10.11591/ijaas.v9.i3.pp180-185.

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In this work two ground-breaking algorithms called; Sperm Motility (SM) algorithm & Wolf Optimization (WO) algorithm is used for solving reactive power problem. In sperm motility approach spontaneous movement of the sperm is imitated & species chemo attractant, sperms are enthralled in the direction of the ovum. In wolf optimization algorithm the deeds of wolf is imitated in the formulation & it has a flag vector also length is equivalent to the whole sum of numbers in the dataset the optimization. Both the projected algorithms have been tested in standard IEEE 57,118, 300 bus test systems. Simulated outcomes reveal about the reduction of real power loss & with variables are in the standard limits. Almost both algorithms solved the problem efficiently, yet wolf optimization has slight edge over the sperm motility algorithm in reducing the real power loss.

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Gajawada, Satish, and Hassan M. H. Mustafa. "Out of the Box Artificial Intelligence (OBAI): The Beginning of a New Era in Artificial Intelligence." Computer and Information Science 15, no. 2 (February 14, 2022): 6. http://dx.doi.org/10.5539/cis.v15n2p6.

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The main purpose of writing this article is to unify all the OUT OF THE BOX ideas (under Artificial Intelligence) invented by the corresponding author of this work during the period (2013-2022) under a single umbrella titled “Out of the BOX Artificial Intelligence Field (OBAI Field)”. All the OUT OF THE BOX ideas which are proposed under Artificial Intelligence will come under new field titled OBAI Field which is defined in this work. A new Artificial Intelligence field titled “Artificial Cartoon Algorithms (ACA)” is invented in this work. ACA is a sub-field of OBAI field as it is an OUT OF THE BOX idea. Four new algorithms titled “Artificial Cartoon Popeye Algorithm”, “Artificial Cartoon Chhota Bheem Algorithm”, “Artificial Cartoon Jerry Algorithm” and “Artificial Cartoon Happy Kid Algorithm” are designed in this work.

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Roy, Shyamal Kumar. "Design and Analysis of P&O algorithm based MPPT solar system in PSIM." YMER Digital 21, no. 06 (June 30, 2022): 1188–94. http://dx.doi.org/10.37896/ymer21.06/b4.

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Conventional solar panels suffer with non-identical losses (resistive losses, diode leakage, loss of material properties etc.). To overcome these unwanted phenomena, a solar maximum power point tracking (MPPT) algorithm has been introduced. In this paper, the algorithms used for tracking the sun (or the solar maximum power point tracking algorithm) has been introduced & a brief description of the basic & easiest algorithm i.e., the P&O Algorithm using PSIM software has been provided to give a clear view about the concept & implementation of MPPT. Keywords: Photovoltaic, MPPT, P&O, PSIM

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Arıcı, FerdaNur, and Ersin Kaya. "Comparison of Meta-heuristic Algorithms on Benchmark Functions." Academic Perspective Procedia 2, no. 3 (November 22, 2019): 508–17. http://dx.doi.org/10.33793/acperpro.02.03.41.

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Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC&rsquo;17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

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Dr Asha Ambhaikar, Mr Abhishek Guru,. "AES AND RSA-BASED HYBRID ALGORITHMS FOR MESSAGE ENCRYPTION & DECRYPTION." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (March 1, 2021): 273–79. http://dx.doi.org/10.17762/itii.v9i1.129.

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File encryption is an easy means of securing personal or business data protection. The RSA and AES representative encryption algorithms are not capable of satisfying the criteria of file encryption reliability and security when used separately. A hybrid encryption algorithm mixing AES and RSA algorithms is suggested in this paper to overcome the above issues in order to solve file encryption performance and security problems. The experimental results suggest that the RSA and AES hybrid encryption algorithm can not only encrypt files, but also provide the benefits of efficiency and protection of the algorithm.

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Chaibou, Amadou, Ousmane Moussa Tessa, and Oumarou Sié. "Modeling the Parallelization of the Edmonds-Karp Algorithm and Application." Computer and Information Science 12, no. 3 (July 25, 2019): 81. http://dx.doi.org/10.5539/cis.v12n3p81.

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Many optimization problems can be reduced to the maximum flow problem in a network. However, the maximum flow problem is equivalent to the problem of the minimum cut, as shown by Fulkerson and Ford (Fulkerson & Ford, 1956). There are several algorithms of the graph’s cut, such as the Ford-Fulkerson algorithm (Ford & Fulkerson, 1962), the Edmonds-Karp algorithm (Edmonds & Karp, 1972) or the Goldberg-Tarjan algorithm (Goldberg & Tarjan, 1988). In this paper, we study the parallel computation of the Edmonds-Karp algorithm which is an optimized version of the Ford-Fulkerson algorithm. Indeed, this algorithm, when executed on large graphs, can be extremely slow, with a complexity of the order of O|V|.|E|2 (where |V| designates the number of vertices and |E| designates the number of the edges of the graph). So why we are studying its implementation on inexpensive parallel platforms such as OpenMp and GP-GPU. Our work also highlights the limits for parallel computing on this algorithm.

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HEJDUCKI, Zdzisław, and Michał PODOLSKI. "SCHEDULING OF CONSTRUCTION PROJECTS WITH APPLICATION OF METAHEURISTIC ALGORITHMS." Scientific Journal of the Military University of Land Forces 166, no. 4 (October 1, 2012): 68–79. http://dx.doi.org/10.5604/01.3001.0002.3530.

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The paper presents the authors’ research on the application of metaheuristic algorithms in Time Coupling Methods (TCM). The experimental analysis of algorithms: tabu search, genetic search, simulated annealing and B&amp;B algorithm was conducted in the paper. The application of these algorithms, which are currently used to solve job scheduling problems, allows one to obtain better suboptimal solutions than with the currently used B&amp;B algorithm. The main branch of the authors’ research is developing the methodology of construction works scheduling with the application of TCM 17,8,9 1013. The problems of scheduling linear construction works using time-cost optimisation are worked out.

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10

Javidian, Mohammad Ali, Marco Valtorta, and Pooyan Jamshidi. "AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms." Journal of Artificial Intelligence Research 69 (October 7, 2020): 419–70. http://dx.doi.org/10.1613/jair.1.12101.

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This paper deals with chain graphs (CGs) under the Andersson–Madigan–Perlman (AMP) interpretation. We address the problem of finding a minimal separator in an AMP CG, namely, finding a set Z of nodes that separates a given non-adjacent pair of nodes such that no proper subset of Z separates that pair. We analyze several versions of this problem and offer polynomial time algorithms for each. These include finding a minimal separator from a restricted set of nodes, finding a minimal separator for two given disjoint sets, and testing whether a given separator is minimal. To address the problem of learning the structure of AMP CGs from data, we show that the PC-like algorithm is order dependent, in the sense that the output can depend on the order in which the variables are given. We propose several modifications of the PC-like algorithm that remove part or all of this order-dependence. We also extend the decomposition-based approach for learning Bayesian networks (BNs) to learn AMP CGs, which include BNs as a special case, under the faithfulness assumption. We prove the correctness of our extension using the minimal separator results. Using standard benchmarks and synthetically generated models and data in our experiments demonstrate the competitive performance of our decomposition-based method, called LCD-AMP, in comparison with the (modified versions of) PC-like algorithm. The LCD-AMP algorithm usually outperforms the PC-like algorithm, and our modifications of the PC-like algorithm learn structures that are more similar to the underlying ground truth graphs than the original PC-like algorithm, especially in high-dimensional settings. In particular, we empirically show that the results of both algorithms are more accurate and stabler when the sample size is reasonably large and the underlying graph is sparse

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11

Diego, Real. "Open path theory: Pattern and structure in prime numbers." Annals of Mathematics and Physics 6, no. 2 (August 25, 2023): 141–48. http://dx.doi.org/10.17352/amp.000093.

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The Open Path theory, supported by experimental data, is presented. The main hypothesis proposes that Prime Numbers's positions are determined by previous Prime Numbers as well as their spacing, in a complex, but deterministic way. The concepts of Open Path, Perfect Space, and Primorial Perfect Space are introduced. The Open Path theory can predict prime gaps of any minimum predetermined size. Two rudimentary algorithms based on this theory are presented. The first algorithm returns a sample (a few hundredth of numbers) containing 25 % of Prime Numbers at distances above 1011. The mirrored sample gives a similar percentage of Prime Numbers. The algorithm execution time is of a few milliseconds. The second algorithm presented determines if a number belonging to a Perfect Space is a composite number or a Prime Number.

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FUJIMURA, Kikuo. "Special Issue: Robot Behavior. Strategy & Algorithm. Motion Strategies and Algorithms." Journal of the Robotics Society of Japan 11, no. 8 (1993): 1124–29. http://dx.doi.org/10.7210/jrsj.11.1124.

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Gilyén, András, Zhao Song, and Ewin Tang. "An improved quantum-inspired algorithm for linear regression." Quantum 6 (June 30, 2022): 754. http://dx.doi.org/10.22331/q-2022-06-30-754.

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We give a classical algorithm for linear regression analogous to the quantum matrix inversion algorithm [Harrow, Hassidim, and Lloyd, Physical Review Letters'09] for low-rank matrices [Wossnig, Zhao, and Prakash, Physical Review Letters'18], when the input matrix A is stored in a data structure applicable for QRAM-based state preparation.Namely, suppose we are given an A∈Cm×n with minimum non-zero singular value σ which supports certain efficient ℓ2-norm importance sampling queries, along with a b∈Cm. Then, for some x∈Cn satisfying ‖x–A+b‖≤ε‖A+b‖, we can output a measurement of |x⟩ in the computational basis and output an entry of x with classical algorithms that run in O~(‖A‖F6‖A‖6σ12ε4) and O~(‖A‖F6‖A‖2σ8ε4) time, respectively. This improves on previous "quantum-inspired" algorithms in this line of research by at least a factor of ‖A‖16σ16ε2 [Chia, Gilyén, Li, Lin, Tang, and Wang, STOC'20]. As a consequence, we show that quantum computers can achieve at most a factor-of-12 speedup for linear regression in this QRAM data structure setting and related settings. Our work applies techniques from sketching algorithms and optimization to the quantum-inspired literature. Unlike earlier works, this is a promising avenue that could lead to feasible implementations of classical regression in a quantum-inspired settings, for comparison against future quantum computers.

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Gajawada, Satish, and Hassan M. H. Mustafa. "Artificial God Optimization - A Creation." Computer and Information Science 13, no. 1 (January 10, 2020): 41. http://dx.doi.org/10.5539/cis.v13n1p41.

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Nature Inspired Optimization Algorithms have become popular for solving complex Optimization problems. Two most popular Global Optimization Algorithms are Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Of the two, PSO is very simple and many Research Scientists have used PSO to solve complex Optimization Problems. Hence PSO is chosen in this work. The primary focus of this paper is on imitating God who created the nature. Hence, the term "Artificial God Optimization (AGO)" is coined in this paper. AGO is a new field, which is invented in this work. A new Algorithm titled "God Particle Swarm Optimization (GoPSO)" is created and applied on various benchmark functions. The World's first Hybrid PSO Algorithm based on Artificial Gods is created in this work. GoPSO is a hybrid Algorithm, which comes under AGO Field as well as PSO Field. Results obtained by PSO are compared with created GoPSO algorithm. A list of opportunities that are available in AGO field for Artificial Intelligence field experts are shown in this work.

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Wang, Meihua, Fengmin Xu, and Chengxian Xu. "A Branch-and-Bound Algorithm Embedded with DCA for DC Programming." Mathematical Problems in Engineering 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/364607.

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The special importance of Difference of Convex (DC) functions programming has been recognized in recent studies on nonconvex optimization problems. In this work, a class of DC programming derived from the portfolio selection problems is studied. The most popular method applied to solve the problem is the Branch-and-Bound (B&B) algorithm. However, “the curse of dimensionality” will affect the performance of the B&B algorithm. DC Algorithm (DCA) is an efficient method to get a local optimal solution. It has been applied to many practical problems, especially for large-scale problems. A B&B-DCA algorithm is proposed by embedding DCA into the B&B algorithms, the new algorithm improves the computational performance and obtains a global optimal solution. Computational results show that the proposed B&B-DCA algorithm has the superiority of the branch number and computational time than general B&B. The nice features of DCA (inexpensiveness, reliability, robustness, globality of computed solutions, etc.) provide crucial support to the combined B&B-DCA for accelerating the convergence of B&B.

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Zhong, Guorong, Xuegang Li, Jinming Song, Baoxiao Qu, Fan Wang, Yanjun Wang, Bin Zhang, et al. "Reconstruction of global surface ocean pCO2 using region-specific predictors based on a stepwise FFNN regression algorithm." Biogeosciences 19, no. 3 (February 10, 2022): 845–59. http://dx.doi.org/10.5194/bg-19-845-2022.

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Abstract. Various machine learning methods were attempted in the global mapping of surface ocean partial pressure of CO2 (pCO2) to reduce the uncertainty of the global ocean CO2 sink estimate due to undersampling of pCO2. In previous research, the predictors of pCO2 were usually selected empirically based on theoretic drivers of surface ocean pCO2, and the same combination of predictors was applied in all areas except where there was a lack of coverage. However, the differences between the drivers of surface ocean pCO2 in different regions were not considered. In this work, we combined the stepwise regression algorithm and a feed-forward neural network (FFNN) to select predictors of pCO2 based on the mean absolute error in each of the 11 biogeochemical provinces defined by the self-organizing map (SOM) method. Based on the predictors selected, a monthly global 1∘ × 1∘ surface ocean pCO2 product from January 1992 to August 2019 was constructed. Validation of different combinations of predictors based on the Surface Ocean CO2 Atlas (SOCAT) dataset version 2020 and independent observations from time series stations was carried out. The prediction of pCO2 based on region-specific predictors selected by the stepwise FFNN algorithm was more precise than that based on predictors from previous research. Applying the FFNN size-improving algorithm in each province decreased the mean absolute error (MAE) of the global estimate to 11.32 µatm and the root mean square error (RMSE) to 17.99 µatm. The script file of the stepwise FFNN algorithm and pCO2 product are distributed through the Institute of Oceanology of the Chinese Academy of Sciences Marine Science Data Center (IOCAS, https://doi.org/10.12157/iocas.2021.0022, Zhong, 2021.

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Awan, Muhammad Mateen Afzal. "Strategic Perturb and Observe Algorithm for Partial Shading Conditions." Sir Syed University Research Journal of Engineering & Technology 12, no. 2 (December 25, 2022): 26–32. http://dx.doi.org/10.33317/ssurj.497.

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Solar photovoltaic (PV) is the cheapest renewable resource of electrical energy. Its dependence on the connected load bounds its production capability. To deliver the determined power, it is required to operate at the maximum power point (MPP) in the characteristic curve of the PV array. Tracking the MPP requires electronic circuits govern by MPP tracking (MPPT) algorithms. The most simple, cheap, and softly implementable MPPT algorithm is “Perturb and Observe (P&O)”. It efficiently performs under uniform weather conditions (UWC) but fails under partial shading conditions (PSC) due to the formation of multiple peaks in the P-V characteristic curve of a PV cell. In this paper, weaknesses of the P&O algorithm are studied and overcome by structural modifications. The proposed structure is named the “strategic P&O algorithm”. Performance of the conventional and proposed algorithms is evaluated at the following standard benchmarks, tracking speed, tracking time, efficiency, and ability to track the GMPP under PSC. Results have shown that the proposed SP&O algorithm has outperformed the conventional P&O algorithm under numerous weather conditions. Simulations are performed in MATLAB/Simulink.

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Hutter, Frank, Lin Xu, Holger H. Hoos, and Kevin Leyton-Brown. "Algorithm runtime prediction: Methods & evaluation." Artificial Intelligence 206 (January 2014): 79–111. http://dx.doi.org/10.1016/j.artint.2013.10.003.

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Kanagasabai, Lenin. "Power loss reduction by arctic wolf optimization algorithm." International Journal of Informatics and Communication Technology (IJ-ICT) 8, no. 3 (November 13, 2019): 111. http://dx.doi.org/10.11591/ijict.v8i3.pp111-116.

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This paper proposes Arctic Wolf optimization (AWO) algorithm to solve the optimal reactive power problem. Deeds of the Arctic wolf have been imitated to formulate the proposed algorithm. Arctic wolf also identified as the white wolf or polar wolf is a breed of gray wolf inhabitant from Melville Island to Ellesmere Island. It is average size, very smaller when compared to north western wolf, it possess whiter coloration, narrower braincase and big carnassials. Particle swarm optimization, Genetic algorithm has been used to improve the Exploration & Exploitation ability of the algorithm by utilizes flag vector & position, velocity update properties. Proposed Arctic Wolf optimization (AWO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the projected algorithms reduced the real power loss considerably.

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Mohtashamzadeh, Mehdi, Mehdi Harizi, and Aref Saiahi. "&quotTraffic analyzer&quot Congestion Control Algorithm for Datacenters." International Journal of Computer Applications 50, no. 23 (July 31, 2012): 19–23. http://dx.doi.org/10.5120/7963-1283.

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Joglekar, Prafulla, Q. B. Chung, and Madjid Tavana. "Note on a comparative evaluation of nine well-known algorithms for solving the cell formation problem in group technology." Journal of Applied Mathematics and Decision Sciences 5, no. 4 (January 1, 2001): 253–68. http://dx.doi.org/10.1155/s1173912601000189.

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Over the last three decades, numerous algorithms have been proposed to solve the work-cell formation problem. For practicing manufacturing managers it would be nice to know as to which algorithm would be most effective and efficient for their specific situation. While several studies have attempted to fulfill this need, most have not resulted in any definitive recommendations and a better methodology of evaluation of cell formation algorithms is urgently needed. Prima facie, the methodology underlying Miltenburg and Zhang's (M&Z) (1991) evaluation of nine well-known cell formation algorithms seems very promising. The primary performance measure proposed by M&Z effectively captures the objectives of a good solution to a cell formation problem and is worthy of use in future studies. Unfortunately, a critical review of M&Z's methodology also reveals certain important flaws in M&Z's methodology. For example, M&Z may not have duplicated each algorithm precisely as the developer(s) of that algorithm intended. Second, M&Z's misrepresent Chandrasekharan and Rajagopalan's [C&R's] (1986) grouping efficiency measure. Third, M&Z's secondary performance measures lead them to unnecessarily ambivalent results. Fourth, several of M&Z's empirical conclusions can be theoretically deduced. It is hoped that future evaluations of cell formation algorithms will benefit from both the strengths and weaknesses of M&Z's work.

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Abu-Taieh, Evon, and Issam AlHadid. "CRUSH: A New Lossless Compression Algorithm." Modern Applied Science 12, no. 11 (October 29, 2018): 387. http://dx.doi.org/10.5539/mas.v12n11p387.

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Multimedia is highly competitive world, one of the properties that is reflected is speed of download and upload of multimedia elements: text, sound, pictures, animation. This paper presents CRUSH algorithm which is a lossless compression algorithm. CRUSH algorithm can be used to compress files. CRUSH method is fast and simple with time complexity O(n) where n is the number of elements being compressed.Furthermore, compressed file is independent from algorithm and unnecessary data structures. As the paper will show comparison with other compression algorithms like Shannon–Fano code, Huffman coding, Run Length Encoding, Arithmetic Coding, Lempel-Ziv-Welch (LZW), Run Length Encoding (RLE), Burrows-Wheeler Transform.Move-to-Front (MTF) Transform, Haar, wavelet tree, Delta Encoding, Rice &Golomb Coding, Tunstall coding, DEFLATE algorithm, Run-Length Golomb-Rice (RLGR).

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Abu-Taieh, Evon, and Issam AlHadid. "CRUSH: A New Lossless Compression Algorithm." Modern Applied Science 12, no. 11 (October 29, 2018): 406. http://dx.doi.org/10.5539/mas.v12n11p406.

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Multimedia is highly competitive world, one of the properties that is reflected is speed of download and upload of multimedia elements: text, sound, pictures, animation. This paper presents CRUSH algorithm which is a lossless compression algorithm. CRUSH algorithm can be used to compress files. CRUSH method is fast and simple with time complexity O(n) where n is the number of elements being compressed.Furthermore, compressed file is independent from algorithm and unnecessary data structures. As the paper will show comparison with other compression algorithms like Shannon–Fano code, Huffman coding, Run Length Encoding, Arithmetic Coding, Lempel-Ziv-Welch (LZW), Run Length Encoding (RLE), Burrows-Wheeler Transform.Move-to-Front (MTF) Transform, Haar, wavelet tree, Delta Encoding, Rice &Golomb Coding, Tunstall coding, DEFLATE algorithm, Run-Length Golomb-Rice (RLGR).

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Bai, Jing Hua, Kan Li, and Xiao Xian Zhang. "On Semi-Supervised Learning Genetic-Based and Deterministic Annealing EM Algorithm for Dirichlet Mixture Models." Applied Mechanics and Materials 39 (November 2010): 151–56. http://dx.doi.org/10.4028/www.scientific.net/amm.39.151.

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We propose a genetic-based and deterministic annealing expectation-maximization (GA&DA-EM) algorithm for learning Dirichlet mixture models from multivariate data. This algorithm is capable of selecting the number of components of the model using the minimum description length (MDL) criterion. Our approach benefits from the properties of Genetic algorithms and deterministic annealing algorithm by combination of both into a single procedure. The population-based stochastic search of the GA&DA explores the search space more thoroughly than the EM method. Therefore, our algorithm enables escaping from local optimal solutions since the algorithm becomes less sensitive to its initialization. The GA&DA-EM algorithm is elitist which maintains the monotonic convergence property of the EM algorithm. We conducted experiments on the WebKB and 20NEWSGROUPS. The results show that show that 1) the GA&DA-EM outperforms the EM method since: Our approach identifies the number of components which were used to generate the underlying data more often than the EM algorithm. 2) the algorithm alternatives to EM that overcoming the challenges of local maxima.

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Shu-Chuan Chu, Shu-Chuan Chu, Qing Feng Shu-Chuan Chu, Jia Zhao Qing Feng, and Jeng-Shyang Pan Jia Zhao. "BFGO: Bamboo Forest Growth Optimization Algorithm." 網際網路技術學刊 24, no. 1 (January 2023): 001–10. http://dx.doi.org/10.53106/160792642023012401001.

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The heuristic optimization algorithm is a popular optimization method for solving optimization problems. However, the main disadvantage of this type of algorithm is the unstable performance, and the performance depends on the specific problem and the designer’s experience, so inappropriate algorithms or parameters will lead to poor performance for solving optimization. In this paper, a new meta-heuristic algorithm—bamboo forest growth optimization (BFGO) algorithm is proposed. The BFGO algorithm refers to the growth law of bamboo: first, take root clearly, and then grow wildly. The growth characteristics of bamboo forests and the optimization process of the algorithm are integrated, and the test is carried out on 30 functions of the CEC2017 test set, and the algorithm is applied to four classical problems of engineering optimization. Compared with well-known heuristic algorithms, the BFGO algorithm has better performance.

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Cheng, J., and M. J. Druzdzel. "AIS-BN: An Adaptive Importance Sampling Algorithm for Evidential Reasoning in Large Bayesian Networks." Journal of Artificial Intelligence Research 13 (October 1, 2000): 155–88. http://dx.doi.org/10.1613/jair.764.

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Stochastic sampling algorithms, while an attractive alternative to exact algorithms in very large Bayesian network models, have been observed to perform poorly in evidential reasoning with extremely unlikely evidence. To address this problem, we propose an adaptive importance sampling algorithm, AIS-BN, that shows promising convergence rates even under extreme conditions and seems to outperform the existing sampling algorithms consistently. Three sources of this performance improvement are (1) two heuristics for initialization of the importance function that are based on the theoretical properties of importance sampling in finite-dimensional integrals and the structural advantages of Bayesian networks, (2) a smooth learning method for the importance function, and (3) a dynamic weighting function for combining samples from different stages of the algorithm. We tested the performance of the AIS-BN algorithm along with two state of the art general purpose sampling algorithms, likelihood weighting (Fung & Chang, 1989; Shachter & Peot, 1989) and self-importance sampling (Shachter & Peot, 1989). We used in our tests three large real Bayesian network models available to the scientific community: the CPCS network (Pradhan et al., 1994), the PathFinder network (Heckerman, Horvitz, & Nathwani, 1990), and the ANDES network (Conati, Gertner, VanLehn, & Druzdzel, 1997), with evidence as unlikely as 10^-41. While the AIS-BN algorithm always performed better than the other two algorithms, in the majority of the test cases it achieved orders of magnitude improvement in precision of the results. Improvement in speed given a desired precision is even more dramatic, although we are unable to report numerical results here, as the other algorithms almost never achieved the precision reached even by the first few iterations of the AIS-BN algorithm.

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Fan, Ti Gui. "The Analysis of Typical Algorithms Based on K-Anonymity." Applied Mechanics and Materials 411-414 (September 2013): 327–30. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.327.

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The backgrounds that K-anonymity was put forward are described. K-anonymity, Quasi Identifier and other related concepts are given. We also analyse the basic algorithms based on K-anonymity such as Datafly algorithm, MinGen (Minimal Generalization) algorithm, Incognito algorithm, Classfly & Classfly+ algorithm, Multiple Constraints algorithm etc, and point out the advantages and flaws of these algorithms. Finally, the future directions in the field are discussed.

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Zenin, V. A., V. V. Eremeev, and A. E. Kuznetcov. "ALGORITHMS FOR RELATIVE RADIOMETRIC CORRECTION IN EARTH OBSERVING SYSTEMS “RESOURCE-P” AND “CANOPUS-V”." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 189–91. http://dx.doi.org/10.5194/isprsarchives-xli-b6-189-2016.

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The present paper has considered two algorithms of the relative radiometric correction of information obtained from a multimatrix imagery instrument of the spacecraft “Resource-P” and frame imagery systems of the spacecraft “Canopus-V”. The first algorithm is intended for elimination of vertical stripes on the image that are caused by difference in transfer characteristics of CCD matrices and CCD detectors. Correction coefficients are determined on the basis of analysis of images that are homogeneous by brightness. The second algorithm ensures an acquisition of microframes homogeneous by brightness from which seamless images of the Earth surface are synthesized. Examples of practical usage of the developed algorithms are mentioned.

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Ekanayake, E. M. U. S. B., W. B. Daundasekara, and S. P. C. Perera. "New Approach to Obtain the Maximum Flow in a Network and Optimal Solution for the Transportation Problems." Modern Applied Science 16, no. 1 (January 21, 2022): 30. http://dx.doi.org/10.5539/mas.v16n1p30.

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The maximum flow problem is also one of the highly regarded problems in the field of optimization theory in which the objective is to find a feasible flow through a flow network that obtains the maximum possible flow rate from source to sink. The literature demonstrates that different techniques have been developed in the past to handle the maximum amount of flow that the network can handle. The Ford-Fulkerson algorithm and Dinic's Algorithm are the two major algorithms for solving these types of problems. Also, the Max-Flow Min-Cut Theorem, the Scaling Algorithm, and the Push–relabel maximum flow algorithm are the most acceptable methods for finding the maximum flows in a flow network. In this novel approach, the paper develops an alternative method of finding the maximum flow between the source and target nodes of a network based on the "max-flow." Also, a new algorithmic approach to solving the transportation problem (minimizing the transportation cost) is based upon the new maximum flow algorithm. It is also to be noticed that this method requires a minimum number of iterations to achieve optimality. This study's algorithmic approach is less complicated than the well-known meta-heuristic algorithms in the literature. 

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Yulan Hu, and Quan Zhang. "Research on Image Segmentation Algorithm Based on Orthogonal Nystr&o&m Algorithm in Target Recognition." Journal of Convergence Information Technology 8, no. 1 (January 15, 2013): 698–704. http://dx.doi.org/10.4156/jcit.vol8.issue1.86.

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Patil, Kirti S. "Sequential Pattern Mining Using Apriori Algorithm & Frequent Pattern Tree Algorithm." IOSR Journal of Engineering 3, no. 01 (January 2013): 26–30. http://dx.doi.org/10.9790/3021-03142630.

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Shobaki, Ghassan, Vahl Scott Gordon, Paul McHugh, Theodore Dubois, and Austin Kerbow. "Register-Pressure-Aware Instruction Scheduling Using Ant Colony Optimization." ACM Transactions on Architecture and Code Optimization 19, no. 2 (June 30, 2022): 1–23. http://dx.doi.org/10.1145/3505558.

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This paper describes a new approach to register-pressure-aware instruction scheduling, using Ant Colony Optimization (ACO) . ACO is a nature-inspired optimization technique that researchers have successfully applied to NP-hard sequencing problems like the Traveling Salesman Problem (TSP) and its derivatives. In this work, we describe an ACO algorithm for solving the long-standing compiler optimization problem of balancing Instruction-Level Parallelism (ILP) and Register Pressure (RP) in pre-allocation instruction scheduling. Three different cost functions are studied for estimating RP during instruction scheduling. The proposed ACO algorithm is implemented in the LLVM open-source compiler, and its performance is evaluated experimentally on three different machines with three different instruction-set architectures: Intel x86, ARM, and AMD GPU. The proposed ACO algorithm is compared to an exact Branch-and-Bound (B&B) algorithm proposed in previous work. On x86 and ARM, both algorithms are evaluated relative to LLVM's generic scheduler, while on the AMD GPU, the algorithms are evaluated relative to AMD's production scheduler. The experimental results show that using SPECrate 2017 Floating Point, the proposed algorithm gives geometric-mean improvements of 1.13% and 1.25% in execution speed on x86 and ARM, respectively, relative to the LLVM scheduler. Using PlaidML on an AMD GPU, it gives a geometric-mean improvement of 7.14% in execution speed relative to the AMD scheduler. The proposed ACO algorithm gives approximately the same execution-time results as the B&B algorithm, with each algorithm outperforming the other on a substantial number of hard scheduling regions. ACO gives better results than B&B on many large instances that B&B times out on. Both ACO and B&B outperform the LLVM algorithm on the CPU and the AMD algorithm on the GPU.

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Rico-Camacho, Roberto I., Luis J. Ricalde, Ali Bassam, Manuel I. Flota-Bañuelos, and Alma Y. Alanis. "Transient Differentiation Maximum Power Point Tracker (Td-MPPT) for Optimized Tracking under Very Fast-Changing Irradiance: A Theoretical Approach for Mobile PV Applications." Applied Sciences 12, no. 5 (March 4, 2022): 2671. http://dx.doi.org/10.3390/app12052671.

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This work presents an algorithm for Maximum Power Point Tracking (MPPT) that measures transitory states to prevent drift issues and that can reduce steady-state oscillations. The traditional MPPT algorithms can become confused under very fast-changing irradiance and perform tracking in the wrong direction. Errors occur because these algorithms operate under the assumption that power changes in the system are triggered exclusively due to perturbations introduced by them. However, the power increase triggered by irradiance changes could be more significant than those caused by the perturbation effect. The proposed method modifies the Perturb and Observe algorithm (P&O) with an additional measurement stage performed close to the maximum overshoot peak after the perturbation stage. By comparing power changes between three measurement points, the algorithm can accurately identify whether the perturbation was made in the correct direction or not. Furthermore, the algorithm can use additional information to determine if the operating point after the perturbation stage is beyond the maximum power point (MPP) and perturb in the opposite direction for the next iteration. Thus, the proposed algorithm shows reduced steady-state oscillations and improved tracking under fast irradiance changes compared to conventional P&O and P&O with power differences (dP-P&O). The design is validated via simulations using fast-changing irradiance tests based on the standard EN 50530 accelerated by a factor of 100×. The proposed algorithm achieved 99.74% of global efficiency versus 97.4% of the classical P&O and 99.54% of the dP-P&O under the tested conditions.

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Lenin, K. "A NOVEL HYBRIDIZED ALGORITHM FOR REDUCTION OF REAL POWER LOSS." International Journal of Research -GRANTHAALAYAH 5, no. 11 (November 30, 2017): 316–24. http://dx.doi.org/10.29121/granthaalayah.v5.i11.2017.2358.

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This paper proposes Hybridization of Gravitational Search algorithm with Simulated Annealing algorithm (HGS) for solving optimal reactive power problem. Individual position modernize strategy in Gravitational Search Algorithm (GSA) may cause damage to the individual position and also the local search capability of GSA is very weak. The new HGS algorithm introduced the idea of Simulated Annealing (SA) into Gravitational Search Algorithm (GSA), which took the Metropolis-principle-based individual position modernize strategy to perk up the particle moves, & after the operation of gravitation, Simulated Annealing operation has been applied to the optimal individual. In order to evaluate the efficiency of the proposed Hybridization of Gravitational Search algorithm with Simulated Annealing algorithm (HGS), it has been tested on standard IEEE 118 & practical 191 bus test systems and compared to the standard reported algorithms. Simulation results show that HGS is superior to other algorithms in reducing the real power loss and voltage profiles also within the limits.

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Lenin, K. "Minimization of real power loss by enhanced teaching learning based optimization algorithm." IAES International Journal of Robotics and Automation (IJRA) 9, no. 1 (March 1, 2020): 1. http://dx.doi.org/10.11591/ijra.v9i1.pp1-5.

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This paper presents an Enhanced Teaching-Learning-Based Optimization (ETLBO) algorithm for solving reactive power flow problem. Basic Teaching-Learning-Based Optimization (TLBO) is reliable, accurate and vigorous for solving the optimization problems. Also it has been found that TLBO algorithm slow in convergence due to its high concentration in the accuracy. This paper presents an, enhanced version of TLBO algorithm, called as enhanced Teaching-Learning-Based Optimization (ETLBO). A parameter called as “weight” has been included in the fundamental TLBO equations & subsequently it increases the rate of convergence. In order to evaluate the proposed algorithm, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results reveal about the better performance of the proposed algorithm in reducing the real power loss & voltage profiles are within the limits.

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Lenin, K. "ACTIVE POWER LOSS REDUCTION BY ASSORTED ALGORITHMS." International Journal of Research -GRANTHAALAYAH 6, no. 5 (May 31, 2018): 263–75. http://dx.doi.org/10.29121/granthaalayah.v6.i5.2018.1448.

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This paper presents assorted algorithms for solving optimal reactive power problem. Symbiosis modeling (SM), which extends the dynamics of the canonical PSO algorithm by adding a significant ingredient that takes into account the symbiotic co evolution between species, Hybridization of Evolutionary algorithm with Conventional Algorithm (HCA) that uses the abilities of evolutionary and conventional algorithm and Genetical Swarm Optimization (GS), which combines Genetic Algorithms (GA) and Particle Swarm Optimization (PSO).All the above said SM, HCA,GS algorithms are used to augment the convergence rate with good Exploration & Exploitation. All the three SM, HCA, GS is applied to Reactive Power optimization problem and has been evaluated in standard IEEE 30 System. The results shows that all the three algorithms perform well in solving the reactive power problem with rapid convergence rate .Of all the three algorithms SM has the slight edge in reducing the real power loss over HCA&GS.

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Yu, Ting Chung, Yih Bin Lin, and Yu Cheng Lin. "Comparisons of the Power-Feedback MPPT Algorithms for the Photovoltaic Systems." Applied Mechanics and Materials 229-231 (November 2012): 1047–51. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1047.

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The purpose of this paper is to compare three power-feedback maximum power point tracking (MPPT) algorithms used in photovoltaic systems. The Matlab/Simulink is used in this paper to establish a model of photovoltaic system with MPPT function. This system is developed by combining the models of established PV module and DC-DC boost converter with the power-feedback MPPT algorithms of perturbation and observation, incremental conductance and hill climbing, respectively. The system will be simulated under different weather conditions and MPPT algorithms. According to the comparisons of the simulation results, it can be observed that the photovoltaic simulation system can track the maximum power accurately using the three MPPT algorithms discussed in this paper. HC algorithm possesses fast dynamic response, but P&O algorithm is well regulated PV output voltage and power than HC algorithm. The tracking time spent by INC algorithm is a little longer than the other two algorithms. The HC algorithm is suitable for the cases of battery charging which doesn't need extremely stable voltage, and the P&O algorithm is more suitable for the system with precision electric instruments. Furthermore, the INC algorithm is adaptable to the cases of fast changing weather conditions owing to its advantage of no misjudgment.

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Abdulrazzaq, Ali Abdulwahhab, and Adnan Hussein Ali. "Efficiency Performances of Two MPPT Algorithms for PV System With Different Solar Panels Irradiancess." International Journal of Power Electronics and Drive Systems (IJPEDS) 9, no. 4 (December 1, 2018): 1755. http://dx.doi.org/10.11591/ijpeds.v9.i4.pp1755-1764.

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A main source of current renewable energy is solar energy. This source of renewable energy can be converted to electrical energy using solar photovoltaic (PV) cells. The Maximum Power Point Tracking (MPPT) earns for maximum energy extractor from PV panels by different irradiance levels. In this paper, overall efficiency of most two popular MPPT techniques utilized in PV applications are analyzed, these algorithms are Perturb and Observe (P&O) and Incremental Conductance (INC). An analysis of the results for the algorithms based on MATLAB simulation for various changes in solar irradiance is performed. Results showed that the efficiency of P&O algorithm was higher than that of the INC, but to obtain the same performance for both, more concentrated calculations should be used for INC. In measuring the output power, current and voltage responses, the use of a solar array having constant and variable irradiations was employed as input for the algorithms. The output waveforms which were derived from a simulation run for the purpose of obtaining the algorithms response to changes in solar array irradiations were compared. In general, the consequences of the P&O algorithm are quiet good and adequate. However, there is a need to improve the algorithm so as to satisfy the requirements of face confident timing in addition to its rapid response so as to make its performance better than that of InCond algorithms.

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Disha Sharma, Disha Sharma. "Comparative Study of RBFS & ARBFS Algorithm." IOSR Journal of Computer Engineering 10, no. 5 (2013): 105–10. http://dx.doi.org/10.9790/0661-105105110.

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Arbel, Julyan, and Igor Prünster. "A moment-matching Ferguson & Klass algorithm." Statistics and Computing 27, no. 1 (June 29, 2016): 3–17. http://dx.doi.org/10.1007/s11222-016-9676-8.

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41

H�yte, Jarle. "The Cut&Glue mesh generation algorithm." Engineering with Computers 8, no. 1 (December 1992): 51–58. http://dx.doi.org/10.1007/bf01206336.

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Danilov, V. V., I. P. Skirnevskiy, R. A. Manakov, D. Y. Kolpashchikov, O. M. Gerget, and A. F. Frangi. "RAY-BASED SEGMENTATION ALGORITHM FOR MEDICAL IMAGING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W12 (May 9, 2019): 37–45. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w12-37-2019.

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Abstract. In this study, we present a segmentation algorithm based on ray casting and border point detection. The algorithm’s main parameter is the number of emitted rays, which defines the resolution of the object’s boundary. The value of this parameter depends on the shape of the target region. For instance, 8 rays are enough to segment the left ventricle with the average Dice similarity coefficient approximately equal to 85%. Having gathered the data of rays, the training datasets had a relatively high level of class imbalance (up to 90%). To cope with this issue, ensemble-based classifiers used to manage imbalanced datasets such as AdaBoost.M2, RUSBoost, UnderBagging, SMOTEBagging, SMOTEBoost were used for border detection. For estimation of the accuracy and processing time, the proposed algorithm used a cardiac MRI dataset of the University of York and brain tumour dataset of Southern Medical University. The highest Dice similarity coefficients for the heart and brain tumour segmentation, equal to 86.5&thinsp;&plusmn;&thinsp;6.9% and 89.5&thinsp;&plusmn;&thinsp;6.7%, respectively, were achieved by the proposed algorithm. The segmentation time of a cardiac frame equals 4.1&thinsp;&plusmn;&thinsp;2.3&thinsp;ms and 20.2&thinsp;&plusmn;&thinsp;23.6&thinsp;ms for 8 and 64 rays, respectively. Brain tumour segmentation took 5.1&thinsp;&plusmn;&thinsp;1.1&thinsp;ms and 16.0&thinsp;&plusmn;&thinsp;3.0&thinsp;ms for 8 and 64 rays respectively. By testing the different medical imaging cases, the proposed algorithm is not time-consuming and highly accurate for convex and closed objects. The scalability of the algorithm allows implementing different border detection techniques working in parallel.

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Lenin, K. "REDUCTION OF ACTIVE POWER LOSS BY IMPROVED TABU SEARCH ALGORITHM." International Journal of Research -GRANTHAALAYAH 6, no. 7 (July 31, 2018): 1–9. http://dx.doi.org/10.29121/granthaalayah.v6.i7.2018.1277.

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In this paper, an Improved Tabu Search (ITS) algorithm has been proposed to solve the optimal reactive power problem. In this work Tabu Search- has been hybridized with Simulated Annealing algorithm to solve the optimal reactive power problem. Hybridization of these two algorithms improves the exploration & exploitation capabilities during the search. Proposed Improved Tabu Search (ITS) algorithm has been tested in Standard IEEE 57,118 bus systems & real power loss has been comparatively reduced with voltage profiles are within the limits.

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Liu, Song, Pieter Valks, Gaia Pinardi, Jian Xu, Ka Lok Chan, Athina Argyrouli, Ronny Lutz, et al. "An improved TROPOMI tropospheric NO2 research product over Europe." Atmospheric Measurement Techniques 14, no. 11 (November 22, 2021): 7297–327. http://dx.doi.org/10.5194/amt-14-7297-2021.

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Abstract. Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

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., KANAKA SIPPORA RANI, and Dr G. RAVINDRANATH . "GLOBAL CONTRAST ENHANCEMENT USING SMI & PR ALGORITHMS." International Journal of Engineering Technology and Management Sciences 6, no. 1 (January 28, 2022): 24–29. http://dx.doi.org/10.46647/ijetms.2022.v06i01.004.

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Image enhancement is one of the challenging issues in low level image processing. In general, it is difficult to design a visual artifact free contrast enhancement method. Considering this, we propose a global, computationally efficient spatial contrast enhancement method which performs enhancement by considering the spatial locations of gray-levels of an image instead of direct use of gray-levels or their co-occurrences. Contrast enhancement is the important factor in image enhancement. Contrast enhancement is used to increase the contrast of an image with low dynamic range and bring out the image details that would be hidden. The enhanced image is looks qualitatively better than the original image if the gray-level differences. This work proposes a novel algorithm, which enhances the low contrast input image by using the spatial information of pixels. This algorithm introduces new method to compute spatial entropy of pixels using spatial distribution of gray levels. This is different than the conventional methods, this algorithm considers the distribution of spatial locations of gray levels of an image instead of gray level distribution or joint statistics computed from gray levels of an image. For each gray level the corresponding spatial distribution is computed by considering spatial location of all pixels having the same gray level in histogram. From the spatial distribution of gray levels of an image entropy can be measured and create distribution which can be further mapped to uniform distribution function to achieve final contrast enhancement. This method achieves contrast enhancement of low contrast image without altering the image if the image’s contrast is high enough. This algorithm considers transform domain coefficient weighting to achieve global and local contrast enhancement of the image. Experimental results show that proposed algorithm produces better enhanced images than existing algorithms.

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Dai, Jing, Fei Fei Guo, and Guo Lin Zhang. "An Improved OFDM Timing Synchronization Algorithm." Applied Mechanics and Materials 220-223 (November 2012): 2419–22. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2419.

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Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier communication system and the system is very sensitive to synchronization errors. The problem that synchronization is not accurate can reduce the system performance largely. Based on the research of Schmidl & Cox and Minn algorithms, the paper proposed an improved timing synchronization algorithm by using the new training sequence in the frequency domain. The improved algorithm eliminates the peak platform problem and side lobe peak problem of the conventional synchronization algorithms in this article. The simulation at MATLAB shows that the improved algorithm overcomes the problems of the conventional algorithms and the timing judgment curve of the improved algorithm also has a very sharp peak at the timing synchronization position, compared with the conventional algorithm. So, the timing synchronization performance of the algorithm is better.

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Pasquale, Nardone, and Sonnino Giorgio. "A simple algorithm for GCD of polynomials." Annals of Mathematics and Physics 5, no. 2 (December 23, 2022): 193–95. http://dx.doi.org/10.17352/amp.000065.

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Based on the Bezout approach we propose a simple algorithm to determine the gcd of two polynomials that don't need division, like the Euclidean algorithm, or determinant calculations, like the Sylvester matrix algorithm. The algorithm needs only n steps for polynomials of degree n. Formal manipulations give the discriminant or the resultant for any degree without needing division or determinant calculation.

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Saberi, Ali, Mehdi Niroomand, and Behzad Mirzaeian Dehkordi. "An Improved P&O Based MPPT for PV Systems with Reduced Steady-State Oscillation." International Journal of Energy Research 2023 (July 22, 2023): 1–15. http://dx.doi.org/10.1155/2023/4694583.

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This paper proposes a perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems. P&O is a simple technique that comes with serious problems, steady-state oscillation, and deviation from the maximum power point (MPP). This algorithm uses variable step size to decrease the convergence time, and it uses the average value of the last three duty cycle to find MPP fast and accurately. In addition, the probability of deviation has been reduced using the direction of the current when the irradiance changes. The irradiance change identifier, steady-state determiner, duty cycle selector, step size alternator, and boundary condition imposer are the extramodules attached to the structure of the original P&O algorithm to change the step size. This algorithm has been tested along with different types of P&O and INC algorithms in MATLAB software and practical experiments using a boost switching converter. The irradiance pattern used in the simulation includes step and slop, increasing and decreasing patterns, and the proposed algorithm obtained an overall efficiency of 98.54%.

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Basha, Alaudeen, and V. Vijayakumar. "Mobile-robot Navigation through Fuzzy Behavioral Algorithm & Vector-polar Histogram Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 3 (March 1, 2018): 565. http://dx.doi.org/10.11591/ijeecs.v9.i3.pp565-571.

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The route of self-governing ground vehicles through general conditions has gotten generous research consideration. Be that as it may, the writing contains not very many correlations of the course ideal models for AGVs, particularly for calculations utilising range discoverers. The fluffy behavioural approach and vector field histogram (VFH) approach are outstanding strategies that can be actualised using range discoverers. This paper will concentrate on looking at their structure, simplicity of programming and calculation tuning, and execution. Both methodologies actualised on a Pioneer 2 robot, outfitted with a SICK laser run discoverer.

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Rachmawati, Dian, Mohammad Andri Budiman, and William Andrei. "Comparison Of RSA Algorithm & Hybrid RSA-OTP Algorithm For Image Security." Journal of Physics: Conference Series 1235 (June 2019): 012076. http://dx.doi.org/10.1088/1742-6596/1235/1/012076.

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Journal articles on the topic 'AMP ALGORITHM'

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